maanasharma5 commited on
Commit
1e8882f
·
verified ·
1 Parent(s): d0b8efd

Upload folder using huggingface_hub

Browse files
Files changed (45) hide show
  1. README.md +202 -0
  2. adapter_config.json +31 -0
  3. adapter_model.safetensors +3 -0
  4. checkpoint-3125/README.md +202 -0
  5. checkpoint-3125/adapter_config.json +31 -0
  6. checkpoint-3125/adapter_model.safetensors +3 -0
  7. checkpoint-3125/merges.txt +0 -0
  8. checkpoint-3125/optimizer.pt +3 -0
  9. checkpoint-3125/rng_state.pth +3 -0
  10. checkpoint-3125/scheduler.pt +3 -0
  11. checkpoint-3125/special_tokens_map.json +24 -0
  12. checkpoint-3125/tokenizer_config.json +22 -0
  13. checkpoint-3125/trainer_state.json +2217 -0
  14. checkpoint-3125/training_args.bin +3 -0
  15. checkpoint-3125/vocab.json +0 -0
  16. checkpoint-6250/README.md +202 -0
  17. checkpoint-6250/adapter_config.json +31 -0
  18. checkpoint-6250/adapter_model.safetensors +3 -0
  19. checkpoint-6250/merges.txt +0 -0
  20. checkpoint-6250/optimizer.pt +3 -0
  21. checkpoint-6250/rng_state.pth +3 -0
  22. checkpoint-6250/scheduler.pt +3 -0
  23. checkpoint-6250/special_tokens_map.json +24 -0
  24. checkpoint-6250/tokenizer_config.json +22 -0
  25. checkpoint-6250/trainer_state.json +0 -0
  26. checkpoint-6250/training_args.bin +3 -0
  27. checkpoint-6250/vocab.json +0 -0
  28. checkpoint-9375/README.md +202 -0
  29. checkpoint-9375/adapter_config.json +31 -0
  30. checkpoint-9375/adapter_model.safetensors +3 -0
  31. checkpoint-9375/merges.txt +0 -0
  32. checkpoint-9375/optimizer.pt +3 -0
  33. checkpoint-9375/rng_state.pth +3 -0
  34. checkpoint-9375/scheduler.pt +3 -0
  35. checkpoint-9375/special_tokens_map.json +24 -0
  36. checkpoint-9375/tokenizer_config.json +22 -0
  37. checkpoint-9375/trainer_state.json +0 -0
  38. checkpoint-9375/training_args.bin +3 -0
  39. checkpoint-9375/vocab.json +0 -0
  40. config.json +40 -0
  41. merges.txt +0 -0
  42. special_tokens_map.json +24 -0
  43. tokenizer_config.json +22 -0
  44. training_logs.csv +939 -0
  45. vocab.json +0 -0
README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: gpt2-medium
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": {
4
+ "base_model_class": "GPT2LMHeadModel",
5
+ "parent_library": "transformers.models.gpt2.modeling_gpt2"
6
+ },
7
+ "base_model_name_or_path": "gpt2-medium",
8
+ "bias": "none",
9
+ "fan_in_fan_out": true,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 128,
17
+ "lora_dropout": 0.0,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": null,
21
+ "peft_type": "LORA",
22
+ "r": 64,
23
+ "rank_pattern": {},
24
+ "revision": null,
25
+ "target_modules": [
26
+ "c_attn"
27
+ ],
28
+ "task_type": null,
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4d1652c7a003dd8627cd4a9648e12d63c6d4c984d8c61b0fca89d4f8de2daeaf
3
+ size 25172088
checkpoint-3125/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: gpt2-medium
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
checkpoint-3125/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": {
4
+ "base_model_class": "GPT2LMHeadModel",
5
+ "parent_library": "transformers.models.gpt2.modeling_gpt2"
6
+ },
7
+ "base_model_name_or_path": "gpt2-medium",
8
+ "bias": "none",
9
+ "fan_in_fan_out": true,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 128,
17
+ "lora_dropout": 0.0,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": null,
21
+ "peft_type": "LORA",
22
+ "r": 64,
23
+ "rank_pattern": {},
24
+ "revision": null,
25
+ "target_modules": [
26
+ "c_attn"
27
+ ],
28
+ "task_type": null,
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
checkpoint-3125/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f6272464f0c1bda6ffa9cdadfef39d61b8b78421f8fcbb6ad2806ad028346120
3
+ size 25172088
checkpoint-3125/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-3125/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cbfa0492104e0d14ab252606a95a1182673ac69bc120fe2d5d982be7311ea6da
3
+ size 50372538
checkpoint-3125/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:feded292b067a53a2aeb0e2a23dd8fd5fd080c27efc2767fe4b430da7e5f7d6f
3
+ size 14244
checkpoint-3125/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:392855cc9cbe029377262097ef598767921e2a3bc6937822c989a7603ee182c3
3
+ size 1064
checkpoint-3125/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<|endoftext|>",
4
+ "lstrip": false,
5
+ "normalized": true,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "<|endoftext|>",
11
+ "lstrip": false,
12
+ "normalized": true,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "<|endoftext|>",
17
+ "unk_token": {
18
+ "content": "<|endoftext|>",
19
+ "lstrip": false,
20
+ "normalized": true,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
checkpoint-3125/tokenizer_config.json ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "50256": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": true,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ }
13
+ },
14
+ "bos_token": "<|endoftext|>",
15
+ "clean_up_tokenization_spaces": false,
16
+ "eos_token": "<|endoftext|>",
17
+ "errors": "replace",
18
+ "model_max_length": 1024,
19
+ "pad_token": "<|endoftext|>",
20
+ "tokenizer_class": "GPT2Tokenizer",
21
+ "unk_token": "<|endoftext|>"
22
+ }
checkpoint-3125/trainer_state.json ADDED
@@ -0,0 +1,2217 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 1.0,
5
+ "eval_steps": 500,
6
+ "global_step": 3125,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.0032,
13
+ "grad_norm": 10.000000953674316,
14
+ "learning_rate": 2.132196162046908e-06,
15
+ "loss": 25.0099,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.0064,
20
+ "grad_norm": 10.0,
21
+ "learning_rate": 4.264392324093816e-06,
22
+ "loss": 21.1499,
23
+ "step": 20
24
+ },
25
+ {
26
+ "epoch": 0.0096,
27
+ "grad_norm": 9.999999046325684,
28
+ "learning_rate": 6.396588486140726e-06,
29
+ "loss": 19.6111,
30
+ "step": 30
31
+ },
32
+ {
33
+ "epoch": 0.0128,
34
+ "grad_norm": 10.0,
35
+ "learning_rate": 8.528784648187633e-06,
36
+ "loss": 22.3722,
37
+ "step": 40
38
+ },
39
+ {
40
+ "epoch": 0.016,
41
+ "grad_norm": 9.999999046325684,
42
+ "learning_rate": 1.0660980810234541e-05,
43
+ "loss": 20.1462,
44
+ "step": 50
45
+ },
46
+ {
47
+ "epoch": 0.0192,
48
+ "grad_norm": 10.0,
49
+ "learning_rate": 1.2793176972281452e-05,
50
+ "loss": 20.4235,
51
+ "step": 60
52
+ },
53
+ {
54
+ "epoch": 0.0224,
55
+ "grad_norm": 10.0,
56
+ "learning_rate": 1.4925373134328357e-05,
57
+ "loss": 20.7853,
58
+ "step": 70
59
+ },
60
+ {
61
+ "epoch": 0.0256,
62
+ "grad_norm": 10.0,
63
+ "learning_rate": 1.7057569296375266e-05,
64
+ "loss": 19.5459,
65
+ "step": 80
66
+ },
67
+ {
68
+ "epoch": 0.0288,
69
+ "grad_norm": 9.999999046325684,
70
+ "learning_rate": 1.9189765458422178e-05,
71
+ "loss": 18.4778,
72
+ "step": 90
73
+ },
74
+ {
75
+ "epoch": 0.032,
76
+ "grad_norm": 9.999999046325684,
77
+ "learning_rate": 2.1321961620469083e-05,
78
+ "loss": 16.2191,
79
+ "step": 100
80
+ },
81
+ {
82
+ "epoch": 0.0352,
83
+ "grad_norm": 10.0,
84
+ "learning_rate": 2.345415778251599e-05,
85
+ "loss": 18.5773,
86
+ "step": 110
87
+ },
88
+ {
89
+ "epoch": 0.0384,
90
+ "grad_norm": 9.999999046325684,
91
+ "learning_rate": 2.5586353944562904e-05,
92
+ "loss": 15.9389,
93
+ "step": 120
94
+ },
95
+ {
96
+ "epoch": 0.0416,
97
+ "grad_norm": 10.0,
98
+ "learning_rate": 2.771855010660981e-05,
99
+ "loss": 15.6064,
100
+ "step": 130
101
+ },
102
+ {
103
+ "epoch": 0.0448,
104
+ "grad_norm": 10.000000953674316,
105
+ "learning_rate": 2.9850746268656714e-05,
106
+ "loss": 15.6366,
107
+ "step": 140
108
+ },
109
+ {
110
+ "epoch": 0.048,
111
+ "grad_norm": 10.000000953674316,
112
+ "learning_rate": 3.1982942430703626e-05,
113
+ "loss": 16.7232,
114
+ "step": 150
115
+ },
116
+ {
117
+ "epoch": 0.0512,
118
+ "grad_norm": 10.0,
119
+ "learning_rate": 3.411513859275053e-05,
120
+ "loss": 13.2957,
121
+ "step": 160
122
+ },
123
+ {
124
+ "epoch": 0.0544,
125
+ "grad_norm": 10.0,
126
+ "learning_rate": 3.624733475479744e-05,
127
+ "loss": 13.3429,
128
+ "step": 170
129
+ },
130
+ {
131
+ "epoch": 0.0576,
132
+ "grad_norm": 9.999999046325684,
133
+ "learning_rate": 3.8379530916844355e-05,
134
+ "loss": 13.3301,
135
+ "step": 180
136
+ },
137
+ {
138
+ "epoch": 0.0608,
139
+ "grad_norm": 10.000000953674316,
140
+ "learning_rate": 4.051172707889126e-05,
141
+ "loss": 15.1708,
142
+ "step": 190
143
+ },
144
+ {
145
+ "epoch": 0.064,
146
+ "grad_norm": 10.0,
147
+ "learning_rate": 4.2643923240938166e-05,
148
+ "loss": 14.8533,
149
+ "step": 200
150
+ },
151
+ {
152
+ "epoch": 0.0672,
153
+ "grad_norm": 10.0,
154
+ "learning_rate": 4.477611940298508e-05,
155
+ "loss": 11.6389,
156
+ "step": 210
157
+ },
158
+ {
159
+ "epoch": 0.0704,
160
+ "grad_norm": 9.999999046325684,
161
+ "learning_rate": 4.690831556503198e-05,
162
+ "loss": 12.2515,
163
+ "step": 220
164
+ },
165
+ {
166
+ "epoch": 0.0736,
167
+ "grad_norm": 10.0,
168
+ "learning_rate": 4.904051172707889e-05,
169
+ "loss": 12.6637,
170
+ "step": 230
171
+ },
172
+ {
173
+ "epoch": 0.0768,
174
+ "grad_norm": 9.999999046325684,
175
+ "learning_rate": 5.117270788912581e-05,
176
+ "loss": 10.6091,
177
+ "step": 240
178
+ },
179
+ {
180
+ "epoch": 0.08,
181
+ "grad_norm": 9.999999046325684,
182
+ "learning_rate": 5.330490405117271e-05,
183
+ "loss": 10.9362,
184
+ "step": 250
185
+ },
186
+ {
187
+ "epoch": 0.0832,
188
+ "grad_norm": 10.0,
189
+ "learning_rate": 5.543710021321962e-05,
190
+ "loss": 12.4545,
191
+ "step": 260
192
+ },
193
+ {
194
+ "epoch": 0.0864,
195
+ "grad_norm": 10.000000953674316,
196
+ "learning_rate": 5.756929637526652e-05,
197
+ "loss": 11.5238,
198
+ "step": 270
199
+ },
200
+ {
201
+ "epoch": 0.0896,
202
+ "grad_norm": 10.0,
203
+ "learning_rate": 5.970149253731343e-05,
204
+ "loss": 10.8966,
205
+ "step": 280
206
+ },
207
+ {
208
+ "epoch": 0.0928,
209
+ "grad_norm": 10.0,
210
+ "learning_rate": 6.183368869936035e-05,
211
+ "loss": 10.5903,
212
+ "step": 290
213
+ },
214
+ {
215
+ "epoch": 0.096,
216
+ "grad_norm": 10.0,
217
+ "learning_rate": 6.396588486140725e-05,
218
+ "loss": 10.4872,
219
+ "step": 300
220
+ },
221
+ {
222
+ "epoch": 0.0992,
223
+ "grad_norm": 10.0,
224
+ "learning_rate": 6.609808102345416e-05,
225
+ "loss": 9.9663,
226
+ "step": 310
227
+ },
228
+ {
229
+ "epoch": 0.1024,
230
+ "grad_norm": 9.999999046325684,
231
+ "learning_rate": 6.823027718550106e-05,
232
+ "loss": 9.4655,
233
+ "step": 320
234
+ },
235
+ {
236
+ "epoch": 0.1056,
237
+ "grad_norm": 10.0,
238
+ "learning_rate": 7.036247334754798e-05,
239
+ "loss": 10.487,
240
+ "step": 330
241
+ },
242
+ {
243
+ "epoch": 0.1088,
244
+ "grad_norm": 10.000001907348633,
245
+ "learning_rate": 7.249466950959489e-05,
246
+ "loss": 9.3626,
247
+ "step": 340
248
+ },
249
+ {
250
+ "epoch": 0.112,
251
+ "grad_norm": 10.0,
252
+ "learning_rate": 7.46268656716418e-05,
253
+ "loss": 9.864,
254
+ "step": 350
255
+ },
256
+ {
257
+ "epoch": 0.1152,
258
+ "grad_norm": 9.999999046325684,
259
+ "learning_rate": 7.675906183368871e-05,
260
+ "loss": 8.8008,
261
+ "step": 360
262
+ },
263
+ {
264
+ "epoch": 0.1184,
265
+ "grad_norm": 10.0,
266
+ "learning_rate": 7.889125799573562e-05,
267
+ "loss": 9.7772,
268
+ "step": 370
269
+ },
270
+ {
271
+ "epoch": 0.1216,
272
+ "grad_norm": 10.0,
273
+ "learning_rate": 8.102345415778252e-05,
274
+ "loss": 8.7418,
275
+ "step": 380
276
+ },
277
+ {
278
+ "epoch": 0.1248,
279
+ "grad_norm": 9.999999046325684,
280
+ "learning_rate": 8.315565031982943e-05,
281
+ "loss": 9.1157,
282
+ "step": 390
283
+ },
284
+ {
285
+ "epoch": 0.128,
286
+ "grad_norm": 10.000000953674316,
287
+ "learning_rate": 8.528784648187633e-05,
288
+ "loss": 8.1395,
289
+ "step": 400
290
+ },
291
+ {
292
+ "epoch": 0.1312,
293
+ "grad_norm": 10.0,
294
+ "learning_rate": 8.742004264392325e-05,
295
+ "loss": 8.8305,
296
+ "step": 410
297
+ },
298
+ {
299
+ "epoch": 0.1344,
300
+ "grad_norm": 10.0,
301
+ "learning_rate": 8.955223880597016e-05,
302
+ "loss": 9.2089,
303
+ "step": 420
304
+ },
305
+ {
306
+ "epoch": 0.1376,
307
+ "grad_norm": 10.000000953674316,
308
+ "learning_rate": 9.168443496801706e-05,
309
+ "loss": 8.5206,
310
+ "step": 430
311
+ },
312
+ {
313
+ "epoch": 0.1408,
314
+ "grad_norm": 9.999999046325684,
315
+ "learning_rate": 9.381663113006397e-05,
316
+ "loss": 8.8993,
317
+ "step": 440
318
+ },
319
+ {
320
+ "epoch": 0.144,
321
+ "grad_norm": 10.0,
322
+ "learning_rate": 9.594882729211087e-05,
323
+ "loss": 8.8173,
324
+ "step": 450
325
+ },
326
+ {
327
+ "epoch": 0.1472,
328
+ "grad_norm": 10.000000953674316,
329
+ "learning_rate": 9.808102345415778e-05,
330
+ "loss": 8.3408,
331
+ "step": 460
332
+ },
333
+ {
334
+ "epoch": 0.1504,
335
+ "grad_norm": 10.0,
336
+ "learning_rate": 9.998877161464182e-05,
337
+ "loss": 7.5853,
338
+ "step": 470
339
+ },
340
+ {
341
+ "epoch": 0.1536,
342
+ "grad_norm": 10.0,
343
+ "learning_rate": 9.987648776105997e-05,
344
+ "loss": 7.4544,
345
+ "step": 480
346
+ },
347
+ {
348
+ "epoch": 0.1568,
349
+ "grad_norm": 10.000000953674316,
350
+ "learning_rate": 9.97642039074781e-05,
351
+ "loss": 8.0499,
352
+ "step": 490
353
+ },
354
+ {
355
+ "epoch": 0.16,
356
+ "grad_norm": 10.0,
357
+ "learning_rate": 9.965192005389625e-05,
358
+ "loss": 8.2335,
359
+ "step": 500
360
+ },
361
+ {
362
+ "epoch": 0.1632,
363
+ "grad_norm": 10.0,
364
+ "learning_rate": 9.95396362003144e-05,
365
+ "loss": 7.0574,
366
+ "step": 510
367
+ },
368
+ {
369
+ "epoch": 0.1664,
370
+ "grad_norm": 10.0,
371
+ "learning_rate": 9.942735234673256e-05,
372
+ "loss": 6.8412,
373
+ "step": 520
374
+ },
375
+ {
376
+ "epoch": 0.1696,
377
+ "grad_norm": 10.0,
378
+ "learning_rate": 9.931506849315069e-05,
379
+ "loss": 7.1418,
380
+ "step": 530
381
+ },
382
+ {
383
+ "epoch": 0.1728,
384
+ "grad_norm": 10.0,
385
+ "learning_rate": 9.920278463956883e-05,
386
+ "loss": 7.1722,
387
+ "step": 540
388
+ },
389
+ {
390
+ "epoch": 0.176,
391
+ "grad_norm": 10.0,
392
+ "learning_rate": 9.909050078598698e-05,
393
+ "loss": 6.7641,
394
+ "step": 550
395
+ },
396
+ {
397
+ "epoch": 0.1792,
398
+ "grad_norm": 10.0,
399
+ "learning_rate": 9.897821693240512e-05,
400
+ "loss": 6.3646,
401
+ "step": 560
402
+ },
403
+ {
404
+ "epoch": 0.1824,
405
+ "grad_norm": 10.0,
406
+ "learning_rate": 9.886593307882327e-05,
407
+ "loss": 6.3469,
408
+ "step": 570
409
+ },
410
+ {
411
+ "epoch": 0.1856,
412
+ "grad_norm": 10.0,
413
+ "learning_rate": 9.875364922524142e-05,
414
+ "loss": 6.38,
415
+ "step": 580
416
+ },
417
+ {
418
+ "epoch": 0.1888,
419
+ "grad_norm": 10.000000953674316,
420
+ "learning_rate": 9.864136537165956e-05,
421
+ "loss": 5.8154,
422
+ "step": 590
423
+ },
424
+ {
425
+ "epoch": 0.192,
426
+ "grad_norm": 10.000000953674316,
427
+ "learning_rate": 9.852908151807771e-05,
428
+ "loss": 5.6794,
429
+ "step": 600
430
+ },
431
+ {
432
+ "epoch": 0.1952,
433
+ "grad_norm": 9.999999046325684,
434
+ "learning_rate": 9.841679766449586e-05,
435
+ "loss": 5.4415,
436
+ "step": 610
437
+ },
438
+ {
439
+ "epoch": 0.1984,
440
+ "grad_norm": 10.0,
441
+ "learning_rate": 9.8304513810914e-05,
442
+ "loss": 4.7814,
443
+ "step": 620
444
+ },
445
+ {
446
+ "epoch": 0.2016,
447
+ "grad_norm": 10.000000953674316,
448
+ "learning_rate": 9.819222995733213e-05,
449
+ "loss": 4.8304,
450
+ "step": 630
451
+ },
452
+ {
453
+ "epoch": 0.2048,
454
+ "grad_norm": 10.0,
455
+ "learning_rate": 9.807994610375028e-05,
456
+ "loss": 4.9017,
457
+ "step": 640
458
+ },
459
+ {
460
+ "epoch": 0.208,
461
+ "grad_norm": 10.0,
462
+ "learning_rate": 9.796766225016843e-05,
463
+ "loss": 4.5826,
464
+ "step": 650
465
+ },
466
+ {
467
+ "epoch": 0.2112,
468
+ "grad_norm": 10.0,
469
+ "learning_rate": 9.785537839658657e-05,
470
+ "loss": 4.4032,
471
+ "step": 660
472
+ },
473
+ {
474
+ "epoch": 0.2144,
475
+ "grad_norm": 10.0,
476
+ "learning_rate": 9.774309454300472e-05,
477
+ "loss": 4.4789,
478
+ "step": 670
479
+ },
480
+ {
481
+ "epoch": 0.2176,
482
+ "grad_norm": 10.000000953674316,
483
+ "learning_rate": 9.763081068942287e-05,
484
+ "loss": 3.5318,
485
+ "step": 680
486
+ },
487
+ {
488
+ "epoch": 0.2208,
489
+ "grad_norm": 10.000000953674316,
490
+ "learning_rate": 9.751852683584101e-05,
491
+ "loss": 3.9803,
492
+ "step": 690
493
+ },
494
+ {
495
+ "epoch": 0.224,
496
+ "grad_norm": 10.0,
497
+ "learning_rate": 9.740624298225916e-05,
498
+ "loss": 3.3411,
499
+ "step": 700
500
+ },
501
+ {
502
+ "epoch": 0.2272,
503
+ "grad_norm": 10.0,
504
+ "learning_rate": 9.729395912867731e-05,
505
+ "loss": 3.8421,
506
+ "step": 710
507
+ },
508
+ {
509
+ "epoch": 0.2304,
510
+ "grad_norm": 10.000000953674316,
511
+ "learning_rate": 9.718167527509545e-05,
512
+ "loss": 3.8598,
513
+ "step": 720
514
+ },
515
+ {
516
+ "epoch": 0.2336,
517
+ "grad_norm": 9.999999046325684,
518
+ "learning_rate": 9.706939142151358e-05,
519
+ "loss": 3.6175,
520
+ "step": 730
521
+ },
522
+ {
523
+ "epoch": 0.2368,
524
+ "grad_norm": 9.999999046325684,
525
+ "learning_rate": 9.695710756793174e-05,
526
+ "loss": 3.3833,
527
+ "step": 740
528
+ },
529
+ {
530
+ "epoch": 0.24,
531
+ "grad_norm": 10.0,
532
+ "learning_rate": 9.684482371434989e-05,
533
+ "loss": 3.1501,
534
+ "step": 750
535
+ },
536
+ {
537
+ "epoch": 0.2432,
538
+ "grad_norm": 10.0,
539
+ "learning_rate": 9.673253986076802e-05,
540
+ "loss": 3.2144,
541
+ "step": 760
542
+ },
543
+ {
544
+ "epoch": 0.2464,
545
+ "grad_norm": 10.0,
546
+ "learning_rate": 9.662025600718617e-05,
547
+ "loss": 3.1372,
548
+ "step": 770
549
+ },
550
+ {
551
+ "epoch": 0.2496,
552
+ "grad_norm": 10.0,
553
+ "learning_rate": 9.650797215360432e-05,
554
+ "loss": 2.728,
555
+ "step": 780
556
+ },
557
+ {
558
+ "epoch": 0.2528,
559
+ "grad_norm": 10.0,
560
+ "learning_rate": 9.639568830002246e-05,
561
+ "loss": 2.7485,
562
+ "step": 790
563
+ },
564
+ {
565
+ "epoch": 0.256,
566
+ "grad_norm": 10.000000953674316,
567
+ "learning_rate": 9.628340444644061e-05,
568
+ "loss": 2.7431,
569
+ "step": 800
570
+ },
571
+ {
572
+ "epoch": 0.2592,
573
+ "grad_norm": 10.0,
574
+ "learning_rate": 9.617112059285875e-05,
575
+ "loss": 2.534,
576
+ "step": 810
577
+ },
578
+ {
579
+ "epoch": 0.2624,
580
+ "grad_norm": 10.0,
581
+ "learning_rate": 9.605883673927689e-05,
582
+ "loss": 2.6129,
583
+ "step": 820
584
+ },
585
+ {
586
+ "epoch": 0.2656,
587
+ "grad_norm": 10.0,
588
+ "learning_rate": 9.594655288569504e-05,
589
+ "loss": 2.6607,
590
+ "step": 830
591
+ },
592
+ {
593
+ "epoch": 0.2688,
594
+ "grad_norm": 9.999999046325684,
595
+ "learning_rate": 9.583426903211319e-05,
596
+ "loss": 2.5158,
597
+ "step": 840
598
+ },
599
+ {
600
+ "epoch": 0.272,
601
+ "grad_norm": 9.999999046325684,
602
+ "learning_rate": 9.572198517853134e-05,
603
+ "loss": 2.2633,
604
+ "step": 850
605
+ },
606
+ {
607
+ "epoch": 0.2752,
608
+ "grad_norm": 10.0,
609
+ "learning_rate": 9.560970132494948e-05,
610
+ "loss": 2.4407,
611
+ "step": 860
612
+ },
613
+ {
614
+ "epoch": 0.2784,
615
+ "grad_norm": 9.999999046325684,
616
+ "learning_rate": 9.549741747136763e-05,
617
+ "loss": 2.1584,
618
+ "step": 870
619
+ },
620
+ {
621
+ "epoch": 0.2816,
622
+ "grad_norm": 10.0,
623
+ "learning_rate": 9.538513361778578e-05,
624
+ "loss": 2.1552,
625
+ "step": 880
626
+ },
627
+ {
628
+ "epoch": 0.2848,
629
+ "grad_norm": 10.000000953674316,
630
+ "learning_rate": 9.527284976420391e-05,
631
+ "loss": 1.8968,
632
+ "step": 890
633
+ },
634
+ {
635
+ "epoch": 0.288,
636
+ "grad_norm": 9.999999046325684,
637
+ "learning_rate": 9.516056591062205e-05,
638
+ "loss": 1.9182,
639
+ "step": 900
640
+ },
641
+ {
642
+ "epoch": 0.2912,
643
+ "grad_norm": 10.0,
644
+ "learning_rate": 9.50482820570402e-05,
645
+ "loss": 1.9413,
646
+ "step": 910
647
+ },
648
+ {
649
+ "epoch": 0.2944,
650
+ "grad_norm": 10.0,
651
+ "learning_rate": 9.493599820345834e-05,
652
+ "loss": 1.8959,
653
+ "step": 920
654
+ },
655
+ {
656
+ "epoch": 0.2976,
657
+ "grad_norm": 10.0,
658
+ "learning_rate": 9.482371434987649e-05,
659
+ "loss": 1.9225,
660
+ "step": 930
661
+ },
662
+ {
663
+ "epoch": 0.3008,
664
+ "grad_norm": 10.0,
665
+ "learning_rate": 9.471143049629464e-05,
666
+ "loss": 1.8802,
667
+ "step": 940
668
+ },
669
+ {
670
+ "epoch": 0.304,
671
+ "grad_norm": 9.999999046325684,
672
+ "learning_rate": 9.459914664271278e-05,
673
+ "loss": 1.8896,
674
+ "step": 950
675
+ },
676
+ {
677
+ "epoch": 0.3072,
678
+ "grad_norm": 10.0,
679
+ "learning_rate": 9.448686278913093e-05,
680
+ "loss": 1.7142,
681
+ "step": 960
682
+ },
683
+ {
684
+ "epoch": 0.3104,
685
+ "grad_norm": 10.0,
686
+ "learning_rate": 9.437457893554908e-05,
687
+ "loss": 1.6888,
688
+ "step": 970
689
+ },
690
+ {
691
+ "epoch": 0.3136,
692
+ "grad_norm": 10.0,
693
+ "learning_rate": 9.426229508196722e-05,
694
+ "loss": 1.6177,
695
+ "step": 980
696
+ },
697
+ {
698
+ "epoch": 0.3168,
699
+ "grad_norm": 10.0,
700
+ "learning_rate": 9.415001122838537e-05,
701
+ "loss": 1.645,
702
+ "step": 990
703
+ },
704
+ {
705
+ "epoch": 0.32,
706
+ "grad_norm": 10.0,
707
+ "learning_rate": 9.40377273748035e-05,
708
+ "loss": 1.6792,
709
+ "step": 1000
710
+ },
711
+ {
712
+ "epoch": 0.3232,
713
+ "grad_norm": 10.0,
714
+ "learning_rate": 9.392544352122165e-05,
715
+ "loss": 1.8599,
716
+ "step": 1010
717
+ },
718
+ {
719
+ "epoch": 0.3264,
720
+ "grad_norm": 10.0,
721
+ "learning_rate": 9.381315966763979e-05,
722
+ "loss": 1.6779,
723
+ "step": 1020
724
+ },
725
+ {
726
+ "epoch": 0.3296,
727
+ "grad_norm": 9.999999046325684,
728
+ "learning_rate": 9.370087581405794e-05,
729
+ "loss": 1.4669,
730
+ "step": 1030
731
+ },
732
+ {
733
+ "epoch": 0.3328,
734
+ "grad_norm": 10.0,
735
+ "learning_rate": 9.358859196047609e-05,
736
+ "loss": 1.3649,
737
+ "step": 1040
738
+ },
739
+ {
740
+ "epoch": 0.336,
741
+ "grad_norm": 10.0,
742
+ "learning_rate": 9.347630810689423e-05,
743
+ "loss": 1.3987,
744
+ "step": 1050
745
+ },
746
+ {
747
+ "epoch": 0.3392,
748
+ "grad_norm": 9.999998092651367,
749
+ "learning_rate": 9.336402425331238e-05,
750
+ "loss": 1.2421,
751
+ "step": 1060
752
+ },
753
+ {
754
+ "epoch": 0.3424,
755
+ "grad_norm": 9.999998092651367,
756
+ "learning_rate": 9.325174039973053e-05,
757
+ "loss": 1.3011,
758
+ "step": 1070
759
+ },
760
+ {
761
+ "epoch": 0.3456,
762
+ "grad_norm": 9.999999046325684,
763
+ "learning_rate": 9.313945654614867e-05,
764
+ "loss": 1.2287,
765
+ "step": 1080
766
+ },
767
+ {
768
+ "epoch": 0.3488,
769
+ "grad_norm": 10.0,
770
+ "learning_rate": 9.30271726925668e-05,
771
+ "loss": 1.1587,
772
+ "step": 1090
773
+ },
774
+ {
775
+ "epoch": 0.352,
776
+ "grad_norm": 10.0,
777
+ "learning_rate": 9.291488883898496e-05,
778
+ "loss": 1.2415,
779
+ "step": 1100
780
+ },
781
+ {
782
+ "epoch": 0.3552,
783
+ "grad_norm": 10.0,
784
+ "learning_rate": 9.280260498540311e-05,
785
+ "loss": 1.1415,
786
+ "step": 1110
787
+ },
788
+ {
789
+ "epoch": 0.3584,
790
+ "grad_norm": 9.999998092651367,
791
+ "learning_rate": 9.269032113182124e-05,
792
+ "loss": 1.1941,
793
+ "step": 1120
794
+ },
795
+ {
796
+ "epoch": 0.3616,
797
+ "grad_norm": 10.0,
798
+ "learning_rate": 9.25780372782394e-05,
799
+ "loss": 1.1668,
800
+ "step": 1130
801
+ },
802
+ {
803
+ "epoch": 0.3648,
804
+ "grad_norm": 10.000000953674316,
805
+ "learning_rate": 9.246575342465755e-05,
806
+ "loss": 1.0887,
807
+ "step": 1140
808
+ },
809
+ {
810
+ "epoch": 0.368,
811
+ "grad_norm": 9.999998092651367,
812
+ "learning_rate": 9.235346957107568e-05,
813
+ "loss": 1.0604,
814
+ "step": 1150
815
+ },
816
+ {
817
+ "epoch": 0.3712,
818
+ "grad_norm": 9.999999046325684,
819
+ "learning_rate": 9.224118571749383e-05,
820
+ "loss": 0.9446,
821
+ "step": 1160
822
+ },
823
+ {
824
+ "epoch": 0.3744,
825
+ "grad_norm": 9.999999046325684,
826
+ "learning_rate": 9.212890186391197e-05,
827
+ "loss": 0.9737,
828
+ "step": 1170
829
+ },
830
+ {
831
+ "epoch": 0.3776,
832
+ "grad_norm": 10.0,
833
+ "learning_rate": 9.201661801033011e-05,
834
+ "loss": 0.9654,
835
+ "step": 1180
836
+ },
837
+ {
838
+ "epoch": 0.3808,
839
+ "grad_norm": 10.000000953674316,
840
+ "learning_rate": 9.190433415674826e-05,
841
+ "loss": 1.0253,
842
+ "step": 1190
843
+ },
844
+ {
845
+ "epoch": 0.384,
846
+ "grad_norm": 9.999999046325684,
847
+ "learning_rate": 9.179205030316641e-05,
848
+ "loss": 0.8597,
849
+ "step": 1200
850
+ },
851
+ {
852
+ "epoch": 0.3872,
853
+ "grad_norm": 9.999998092651367,
854
+ "learning_rate": 9.167976644958456e-05,
855
+ "loss": 0.8202,
856
+ "step": 1210
857
+ },
858
+ {
859
+ "epoch": 0.3904,
860
+ "grad_norm": 9.999999046325684,
861
+ "learning_rate": 9.15674825960027e-05,
862
+ "loss": 0.8386,
863
+ "step": 1220
864
+ },
865
+ {
866
+ "epoch": 0.3936,
867
+ "grad_norm": 9.999999046325684,
868
+ "learning_rate": 9.145519874242085e-05,
869
+ "loss": 0.8318,
870
+ "step": 1230
871
+ },
872
+ {
873
+ "epoch": 0.3968,
874
+ "grad_norm": 10.0,
875
+ "learning_rate": 9.1342914888839e-05,
876
+ "loss": 0.8571,
877
+ "step": 1240
878
+ },
879
+ {
880
+ "epoch": 0.4,
881
+ "grad_norm": 9.999999046325684,
882
+ "learning_rate": 9.123063103525713e-05,
883
+ "loss": 0.8326,
884
+ "step": 1250
885
+ },
886
+ {
887
+ "epoch": 0.4032,
888
+ "grad_norm": 9.999999046325684,
889
+ "learning_rate": 9.111834718167527e-05,
890
+ "loss": 0.7655,
891
+ "step": 1260
892
+ },
893
+ {
894
+ "epoch": 0.4064,
895
+ "grad_norm": 10.0,
896
+ "learning_rate": 9.100606332809342e-05,
897
+ "loss": 0.747,
898
+ "step": 1270
899
+ },
900
+ {
901
+ "epoch": 0.4096,
902
+ "grad_norm": 10.0,
903
+ "learning_rate": 9.089377947451156e-05,
904
+ "loss": 0.8671,
905
+ "step": 1280
906
+ },
907
+ {
908
+ "epoch": 0.4128,
909
+ "grad_norm": 9.999999046325684,
910
+ "learning_rate": 9.078149562092971e-05,
911
+ "loss": 0.8758,
912
+ "step": 1290
913
+ },
914
+ {
915
+ "epoch": 0.416,
916
+ "grad_norm": 10.000000953674316,
917
+ "learning_rate": 9.066921176734786e-05,
918
+ "loss": 0.8714,
919
+ "step": 1300
920
+ },
921
+ {
922
+ "epoch": 0.4192,
923
+ "grad_norm": 9.999999046325684,
924
+ "learning_rate": 9.055692791376601e-05,
925
+ "loss": 0.8022,
926
+ "step": 1310
927
+ },
928
+ {
929
+ "epoch": 0.4224,
930
+ "grad_norm": 8.615378379821777,
931
+ "learning_rate": 9.044464406018415e-05,
932
+ "loss": 0.7234,
933
+ "step": 1320
934
+ },
935
+ {
936
+ "epoch": 0.4256,
937
+ "grad_norm": 10.0,
938
+ "learning_rate": 9.03323602066023e-05,
939
+ "loss": 0.7416,
940
+ "step": 1330
941
+ },
942
+ {
943
+ "epoch": 0.4288,
944
+ "grad_norm": 10.0,
945
+ "learning_rate": 9.022007635302045e-05,
946
+ "loss": 0.6898,
947
+ "step": 1340
948
+ },
949
+ {
950
+ "epoch": 0.432,
951
+ "grad_norm": 9.999999046325684,
952
+ "learning_rate": 9.010779249943859e-05,
953
+ "loss": 0.6261,
954
+ "step": 1350
955
+ },
956
+ {
957
+ "epoch": 0.4352,
958
+ "grad_norm": 10.0,
959
+ "learning_rate": 8.999550864585672e-05,
960
+ "loss": 0.6267,
961
+ "step": 1360
962
+ },
963
+ {
964
+ "epoch": 0.4384,
965
+ "grad_norm": 9.999999046325684,
966
+ "learning_rate": 8.988322479227488e-05,
967
+ "loss": 0.6171,
968
+ "step": 1370
969
+ },
970
+ {
971
+ "epoch": 0.4416,
972
+ "grad_norm": 9.999998092651367,
973
+ "learning_rate": 8.977094093869301e-05,
974
+ "loss": 0.5677,
975
+ "step": 1380
976
+ },
977
+ {
978
+ "epoch": 0.4448,
979
+ "grad_norm": 9.999999046325684,
980
+ "learning_rate": 8.965865708511116e-05,
981
+ "loss": 0.5227,
982
+ "step": 1390
983
+ },
984
+ {
985
+ "epoch": 0.448,
986
+ "grad_norm": 9.999999046325684,
987
+ "learning_rate": 8.954637323152931e-05,
988
+ "loss": 0.5775,
989
+ "step": 1400
990
+ },
991
+ {
992
+ "epoch": 0.4512,
993
+ "grad_norm": 9.999998092651367,
994
+ "learning_rate": 8.943408937794746e-05,
995
+ "loss": 0.6166,
996
+ "step": 1410
997
+ },
998
+ {
999
+ "epoch": 0.4544,
1000
+ "grad_norm": 10.0,
1001
+ "learning_rate": 8.93218055243656e-05,
1002
+ "loss": 0.6165,
1003
+ "step": 1420
1004
+ },
1005
+ {
1006
+ "epoch": 0.4576,
1007
+ "grad_norm": 9.999999046325684,
1008
+ "learning_rate": 8.920952167078375e-05,
1009
+ "loss": 0.5849,
1010
+ "step": 1430
1011
+ },
1012
+ {
1013
+ "epoch": 0.4608,
1014
+ "grad_norm": 10.0,
1015
+ "learning_rate": 8.909723781720189e-05,
1016
+ "loss": 0.6439,
1017
+ "step": 1440
1018
+ },
1019
+ {
1020
+ "epoch": 0.464,
1021
+ "grad_norm": 9.999998092651367,
1022
+ "learning_rate": 8.898495396362003e-05,
1023
+ "loss": 0.5886,
1024
+ "step": 1450
1025
+ },
1026
+ {
1027
+ "epoch": 0.4672,
1028
+ "grad_norm": 9.999999046325684,
1029
+ "learning_rate": 8.887267011003818e-05,
1030
+ "loss": 0.5935,
1031
+ "step": 1460
1032
+ },
1033
+ {
1034
+ "epoch": 0.4704,
1035
+ "grad_norm": 10.0,
1036
+ "learning_rate": 8.876038625645633e-05,
1037
+ "loss": 0.5868,
1038
+ "step": 1470
1039
+ },
1040
+ {
1041
+ "epoch": 0.4736,
1042
+ "grad_norm": 9.999998092651367,
1043
+ "learning_rate": 8.864810240287447e-05,
1044
+ "loss": 0.5489,
1045
+ "step": 1480
1046
+ },
1047
+ {
1048
+ "epoch": 0.4768,
1049
+ "grad_norm": 10.0,
1050
+ "learning_rate": 8.853581854929262e-05,
1051
+ "loss": 0.5106,
1052
+ "step": 1490
1053
+ },
1054
+ {
1055
+ "epoch": 0.48,
1056
+ "grad_norm": 9.999999046325684,
1057
+ "learning_rate": 8.842353469571077e-05,
1058
+ "loss": 0.4885,
1059
+ "step": 1500
1060
+ },
1061
+ {
1062
+ "epoch": 0.4832,
1063
+ "grad_norm": 9.999999046325684,
1064
+ "learning_rate": 8.83112508421289e-05,
1065
+ "loss": 0.5323,
1066
+ "step": 1510
1067
+ },
1068
+ {
1069
+ "epoch": 0.4864,
1070
+ "grad_norm": 9.999999046325684,
1071
+ "learning_rate": 8.819896698854705e-05,
1072
+ "loss": 0.4359,
1073
+ "step": 1520
1074
+ },
1075
+ {
1076
+ "epoch": 0.4896,
1077
+ "grad_norm": 7.423900604248047,
1078
+ "learning_rate": 8.808668313496519e-05,
1079
+ "loss": 0.4789,
1080
+ "step": 1530
1081
+ },
1082
+ {
1083
+ "epoch": 0.4928,
1084
+ "grad_norm": 9.999998092651367,
1085
+ "learning_rate": 8.797439928138334e-05,
1086
+ "loss": 0.4367,
1087
+ "step": 1540
1088
+ },
1089
+ {
1090
+ "epoch": 0.496,
1091
+ "grad_norm": 7.3594489097595215,
1092
+ "learning_rate": 8.786211542780148e-05,
1093
+ "loss": 0.465,
1094
+ "step": 1550
1095
+ },
1096
+ {
1097
+ "epoch": 0.4992,
1098
+ "grad_norm": 9.999998092651367,
1099
+ "learning_rate": 8.774983157421963e-05,
1100
+ "loss": 0.4244,
1101
+ "step": 1560
1102
+ },
1103
+ {
1104
+ "epoch": 0.5024,
1105
+ "grad_norm": 10.0,
1106
+ "learning_rate": 8.763754772063778e-05,
1107
+ "loss": 0.4311,
1108
+ "step": 1570
1109
+ },
1110
+ {
1111
+ "epoch": 0.5056,
1112
+ "grad_norm": 9.999999046325684,
1113
+ "learning_rate": 8.752526386705592e-05,
1114
+ "loss": 0.4787,
1115
+ "step": 1580
1116
+ },
1117
+ {
1118
+ "epoch": 0.5088,
1119
+ "grad_norm": 9.999999046325684,
1120
+ "learning_rate": 8.741298001347407e-05,
1121
+ "loss": 0.4777,
1122
+ "step": 1590
1123
+ },
1124
+ {
1125
+ "epoch": 0.512,
1126
+ "grad_norm": 10.0,
1127
+ "learning_rate": 8.730069615989222e-05,
1128
+ "loss": 0.469,
1129
+ "step": 1600
1130
+ },
1131
+ {
1132
+ "epoch": 0.5152,
1133
+ "grad_norm": 10.0,
1134
+ "learning_rate": 8.718841230631036e-05,
1135
+ "loss": 0.4519,
1136
+ "step": 1610
1137
+ },
1138
+ {
1139
+ "epoch": 0.5184,
1140
+ "grad_norm": 9.999998092651367,
1141
+ "learning_rate": 8.70761284527285e-05,
1142
+ "loss": 0.4084,
1143
+ "step": 1620
1144
+ },
1145
+ {
1146
+ "epoch": 0.5216,
1147
+ "grad_norm": 9.999998092651367,
1148
+ "learning_rate": 8.696384459914664e-05,
1149
+ "loss": 0.3627,
1150
+ "step": 1630
1151
+ },
1152
+ {
1153
+ "epoch": 0.5248,
1154
+ "grad_norm": 8.502776145935059,
1155
+ "learning_rate": 8.68515607455648e-05,
1156
+ "loss": 0.3742,
1157
+ "step": 1640
1158
+ },
1159
+ {
1160
+ "epoch": 0.528,
1161
+ "grad_norm": 10.0,
1162
+ "learning_rate": 8.673927689198293e-05,
1163
+ "loss": 0.3525,
1164
+ "step": 1650
1165
+ },
1166
+ {
1167
+ "epoch": 0.5312,
1168
+ "grad_norm": 9.999999046325684,
1169
+ "learning_rate": 8.662699303840108e-05,
1170
+ "loss": 0.3889,
1171
+ "step": 1660
1172
+ },
1173
+ {
1174
+ "epoch": 0.5344,
1175
+ "grad_norm": 10.0,
1176
+ "learning_rate": 8.651470918481923e-05,
1177
+ "loss": 0.5584,
1178
+ "step": 1670
1179
+ },
1180
+ {
1181
+ "epoch": 0.5376,
1182
+ "grad_norm": 9.999999046325684,
1183
+ "learning_rate": 8.640242533123737e-05,
1184
+ "loss": 0.3988,
1185
+ "step": 1680
1186
+ },
1187
+ {
1188
+ "epoch": 0.5408,
1189
+ "grad_norm": 8.782861709594727,
1190
+ "learning_rate": 8.629014147765552e-05,
1191
+ "loss": 0.3439,
1192
+ "step": 1690
1193
+ },
1194
+ {
1195
+ "epoch": 0.544,
1196
+ "grad_norm": 8.174032211303711,
1197
+ "learning_rate": 8.617785762407367e-05,
1198
+ "loss": 0.3265,
1199
+ "step": 1700
1200
+ },
1201
+ {
1202
+ "epoch": 0.5472,
1203
+ "grad_norm": 4.737403392791748,
1204
+ "learning_rate": 8.606557377049181e-05,
1205
+ "loss": 0.329,
1206
+ "step": 1710
1207
+ },
1208
+ {
1209
+ "epoch": 0.5504,
1210
+ "grad_norm": 9.999999046325684,
1211
+ "learning_rate": 8.595328991690995e-05,
1212
+ "loss": 0.3093,
1213
+ "step": 1720
1214
+ },
1215
+ {
1216
+ "epoch": 0.5536,
1217
+ "grad_norm": 10.0,
1218
+ "learning_rate": 8.58410060633281e-05,
1219
+ "loss": 0.3119,
1220
+ "step": 1730
1221
+ },
1222
+ {
1223
+ "epoch": 0.5568,
1224
+ "grad_norm": 10.0,
1225
+ "learning_rate": 8.572872220974623e-05,
1226
+ "loss": 0.3227,
1227
+ "step": 1740
1228
+ },
1229
+ {
1230
+ "epoch": 0.56,
1231
+ "grad_norm": 9.882418632507324,
1232
+ "learning_rate": 8.561643835616438e-05,
1233
+ "loss": 0.2979,
1234
+ "step": 1750
1235
+ },
1236
+ {
1237
+ "epoch": 0.5632,
1238
+ "grad_norm": 9.999998092651367,
1239
+ "learning_rate": 8.550415450258253e-05,
1240
+ "loss": 0.2693,
1241
+ "step": 1760
1242
+ },
1243
+ {
1244
+ "epoch": 0.5664,
1245
+ "grad_norm": 9.999999046325684,
1246
+ "learning_rate": 8.539187064900069e-05,
1247
+ "loss": 0.3187,
1248
+ "step": 1770
1249
+ },
1250
+ {
1251
+ "epoch": 0.5696,
1252
+ "grad_norm": 9.999999046325684,
1253
+ "learning_rate": 8.527958679541882e-05,
1254
+ "loss": 0.291,
1255
+ "step": 1780
1256
+ },
1257
+ {
1258
+ "epoch": 0.5728,
1259
+ "grad_norm": 7.839264869689941,
1260
+ "learning_rate": 8.516730294183697e-05,
1261
+ "loss": 0.2833,
1262
+ "step": 1790
1263
+ },
1264
+ {
1265
+ "epoch": 0.576,
1266
+ "grad_norm": 4.611258029937744,
1267
+ "learning_rate": 8.505501908825511e-05,
1268
+ "loss": 0.2525,
1269
+ "step": 1800
1270
+ },
1271
+ {
1272
+ "epoch": 0.5792,
1273
+ "grad_norm": 4.125186443328857,
1274
+ "learning_rate": 8.494273523467325e-05,
1275
+ "loss": 0.2727,
1276
+ "step": 1810
1277
+ },
1278
+ {
1279
+ "epoch": 0.5824,
1280
+ "grad_norm": 9.999999046325684,
1281
+ "learning_rate": 8.48304513810914e-05,
1282
+ "loss": 0.2718,
1283
+ "step": 1820
1284
+ },
1285
+ {
1286
+ "epoch": 0.5856,
1287
+ "grad_norm": 9.999999046325684,
1288
+ "learning_rate": 8.471816752750955e-05,
1289
+ "loss": 0.2787,
1290
+ "step": 1830
1291
+ },
1292
+ {
1293
+ "epoch": 0.5888,
1294
+ "grad_norm": 4.507540225982666,
1295
+ "learning_rate": 8.460588367392769e-05,
1296
+ "loss": 0.2903,
1297
+ "step": 1840
1298
+ },
1299
+ {
1300
+ "epoch": 0.592,
1301
+ "grad_norm": 8.763723373413086,
1302
+ "learning_rate": 8.449359982034584e-05,
1303
+ "loss": 0.2821,
1304
+ "step": 1850
1305
+ },
1306
+ {
1307
+ "epoch": 0.5952,
1308
+ "grad_norm": 6.04974365234375,
1309
+ "learning_rate": 8.438131596676399e-05,
1310
+ "loss": 0.2469,
1311
+ "step": 1860
1312
+ },
1313
+ {
1314
+ "epoch": 0.5984,
1315
+ "grad_norm": 9.999998092651367,
1316
+ "learning_rate": 8.426903211318214e-05,
1317
+ "loss": 0.2389,
1318
+ "step": 1870
1319
+ },
1320
+ {
1321
+ "epoch": 0.6016,
1322
+ "grad_norm": 10.0,
1323
+ "learning_rate": 8.415674825960028e-05,
1324
+ "loss": 0.2749,
1325
+ "step": 1880
1326
+ },
1327
+ {
1328
+ "epoch": 0.6048,
1329
+ "grad_norm": 10.0,
1330
+ "learning_rate": 8.404446440601843e-05,
1331
+ "loss": 0.2829,
1332
+ "step": 1890
1333
+ },
1334
+ {
1335
+ "epoch": 0.608,
1336
+ "grad_norm": 9.99999713897705,
1337
+ "learning_rate": 8.393218055243656e-05,
1338
+ "loss": 0.2725,
1339
+ "step": 1900
1340
+ },
1341
+ {
1342
+ "epoch": 0.6112,
1343
+ "grad_norm": 10.000001907348633,
1344
+ "learning_rate": 8.38198966988547e-05,
1345
+ "loss": 0.2698,
1346
+ "step": 1910
1347
+ },
1348
+ {
1349
+ "epoch": 0.6144,
1350
+ "grad_norm": 9.999999046325684,
1351
+ "learning_rate": 8.370761284527285e-05,
1352
+ "loss": 0.2678,
1353
+ "step": 1920
1354
+ },
1355
+ {
1356
+ "epoch": 0.6176,
1357
+ "grad_norm": 10.0,
1358
+ "learning_rate": 8.3595328991691e-05,
1359
+ "loss": 0.2741,
1360
+ "step": 1930
1361
+ },
1362
+ {
1363
+ "epoch": 0.6208,
1364
+ "grad_norm": 10.0,
1365
+ "learning_rate": 8.348304513810914e-05,
1366
+ "loss": 0.2475,
1367
+ "step": 1940
1368
+ },
1369
+ {
1370
+ "epoch": 0.624,
1371
+ "grad_norm": 9.999999046325684,
1372
+ "learning_rate": 8.337076128452729e-05,
1373
+ "loss": 0.2711,
1374
+ "step": 1950
1375
+ },
1376
+ {
1377
+ "epoch": 0.6272,
1378
+ "grad_norm": 10.0,
1379
+ "learning_rate": 8.325847743094544e-05,
1380
+ "loss": 0.2592,
1381
+ "step": 1960
1382
+ },
1383
+ {
1384
+ "epoch": 0.6304,
1385
+ "grad_norm": 9.999999046325684,
1386
+ "learning_rate": 8.314619357736358e-05,
1387
+ "loss": 0.2348,
1388
+ "step": 1970
1389
+ },
1390
+ {
1391
+ "epoch": 0.6336,
1392
+ "grad_norm": 7.087158679962158,
1393
+ "learning_rate": 8.303390972378173e-05,
1394
+ "loss": 0.2185,
1395
+ "step": 1980
1396
+ },
1397
+ {
1398
+ "epoch": 0.6368,
1399
+ "grad_norm": 6.557620048522949,
1400
+ "learning_rate": 8.292162587019986e-05,
1401
+ "loss": 0.2443,
1402
+ "step": 1990
1403
+ },
1404
+ {
1405
+ "epoch": 0.64,
1406
+ "grad_norm": 9.999999046325684,
1407
+ "learning_rate": 8.280934201661802e-05,
1408
+ "loss": 0.2012,
1409
+ "step": 2000
1410
+ },
1411
+ {
1412
+ "epoch": 0.6432,
1413
+ "grad_norm": 8.828990936279297,
1414
+ "learning_rate": 8.269705816303615e-05,
1415
+ "loss": 0.1992,
1416
+ "step": 2010
1417
+ },
1418
+ {
1419
+ "epoch": 0.6464,
1420
+ "grad_norm": 9.999998092651367,
1421
+ "learning_rate": 8.25847743094543e-05,
1422
+ "loss": 0.2005,
1423
+ "step": 2020
1424
+ },
1425
+ {
1426
+ "epoch": 0.6496,
1427
+ "grad_norm": 10.0,
1428
+ "learning_rate": 8.247249045587245e-05,
1429
+ "loss": 0.2244,
1430
+ "step": 2030
1431
+ },
1432
+ {
1433
+ "epoch": 0.6528,
1434
+ "grad_norm": 10.0,
1435
+ "learning_rate": 8.236020660229059e-05,
1436
+ "loss": 0.3351,
1437
+ "step": 2040
1438
+ },
1439
+ {
1440
+ "epoch": 0.656,
1441
+ "grad_norm": 10.0,
1442
+ "learning_rate": 8.224792274870874e-05,
1443
+ "loss": 0.3391,
1444
+ "step": 2050
1445
+ },
1446
+ {
1447
+ "epoch": 0.6592,
1448
+ "grad_norm": 9.999998092651367,
1449
+ "learning_rate": 8.213563889512689e-05,
1450
+ "loss": 0.2319,
1451
+ "step": 2060
1452
+ },
1453
+ {
1454
+ "epoch": 0.6624,
1455
+ "grad_norm": 10.0,
1456
+ "learning_rate": 8.202335504154503e-05,
1457
+ "loss": 0.2222,
1458
+ "step": 2070
1459
+ },
1460
+ {
1461
+ "epoch": 0.6656,
1462
+ "grad_norm": 8.043660163879395,
1463
+ "learning_rate": 8.191107118796317e-05,
1464
+ "loss": 0.1829,
1465
+ "step": 2080
1466
+ },
1467
+ {
1468
+ "epoch": 0.6688,
1469
+ "grad_norm": 5.343007564544678,
1470
+ "learning_rate": 8.179878733438132e-05,
1471
+ "loss": 0.1756,
1472
+ "step": 2090
1473
+ },
1474
+ {
1475
+ "epoch": 0.672,
1476
+ "grad_norm": 3.530430316925049,
1477
+ "learning_rate": 8.168650348079947e-05,
1478
+ "loss": 0.1959,
1479
+ "step": 2100
1480
+ },
1481
+ {
1482
+ "epoch": 0.6752,
1483
+ "grad_norm": 9.999999046325684,
1484
+ "learning_rate": 8.15742196272176e-05,
1485
+ "loss": 0.178,
1486
+ "step": 2110
1487
+ },
1488
+ {
1489
+ "epoch": 0.6784,
1490
+ "grad_norm": 10.0,
1491
+ "learning_rate": 8.146193577363576e-05,
1492
+ "loss": 0.1867,
1493
+ "step": 2120
1494
+ },
1495
+ {
1496
+ "epoch": 0.6816,
1497
+ "grad_norm": 8.584357261657715,
1498
+ "learning_rate": 8.13496519200539e-05,
1499
+ "loss": 0.1832,
1500
+ "step": 2130
1501
+ },
1502
+ {
1503
+ "epoch": 0.6848,
1504
+ "grad_norm": 4.891357421875,
1505
+ "learning_rate": 8.123736806647204e-05,
1506
+ "loss": 0.1771,
1507
+ "step": 2140
1508
+ },
1509
+ {
1510
+ "epoch": 0.688,
1511
+ "grad_norm": 5.522593021392822,
1512
+ "learning_rate": 8.11250842128902e-05,
1513
+ "loss": 0.1527,
1514
+ "step": 2150
1515
+ },
1516
+ {
1517
+ "epoch": 0.6912,
1518
+ "grad_norm": 9.386947631835938,
1519
+ "learning_rate": 8.101280035930835e-05,
1520
+ "loss": 0.1769,
1521
+ "step": 2160
1522
+ },
1523
+ {
1524
+ "epoch": 0.6944,
1525
+ "grad_norm": 10.0,
1526
+ "learning_rate": 8.090051650572648e-05,
1527
+ "loss": 0.1889,
1528
+ "step": 2170
1529
+ },
1530
+ {
1531
+ "epoch": 0.6976,
1532
+ "grad_norm": 9.999999046325684,
1533
+ "learning_rate": 8.078823265214462e-05,
1534
+ "loss": 0.1827,
1535
+ "step": 2180
1536
+ },
1537
+ {
1538
+ "epoch": 0.7008,
1539
+ "grad_norm": 9.999999046325684,
1540
+ "learning_rate": 8.067594879856277e-05,
1541
+ "loss": 0.2055,
1542
+ "step": 2190
1543
+ },
1544
+ {
1545
+ "epoch": 0.704,
1546
+ "grad_norm": 9.999998092651367,
1547
+ "learning_rate": 8.056366494498092e-05,
1548
+ "loss": 0.1802,
1549
+ "step": 2200
1550
+ },
1551
+ {
1552
+ "epoch": 0.7072,
1553
+ "grad_norm": 9.999999046325684,
1554
+ "learning_rate": 8.045138109139906e-05,
1555
+ "loss": 0.1706,
1556
+ "step": 2210
1557
+ },
1558
+ {
1559
+ "epoch": 0.7104,
1560
+ "grad_norm": 3.970720052719116,
1561
+ "learning_rate": 8.033909723781721e-05,
1562
+ "loss": 0.1604,
1563
+ "step": 2220
1564
+ },
1565
+ {
1566
+ "epoch": 0.7136,
1567
+ "grad_norm": 3.6069769859313965,
1568
+ "learning_rate": 8.022681338423536e-05,
1569
+ "loss": 0.1453,
1570
+ "step": 2230
1571
+ },
1572
+ {
1573
+ "epoch": 0.7168,
1574
+ "grad_norm": 3.9357783794403076,
1575
+ "learning_rate": 8.01145295306535e-05,
1576
+ "loss": 0.1516,
1577
+ "step": 2240
1578
+ },
1579
+ {
1580
+ "epoch": 0.72,
1581
+ "grad_norm": 5.958951950073242,
1582
+ "learning_rate": 8.000224567707165e-05,
1583
+ "loss": 0.1512,
1584
+ "step": 2250
1585
+ },
1586
+ {
1587
+ "epoch": 0.7232,
1588
+ "grad_norm": 9.320231437683105,
1589
+ "learning_rate": 7.988996182348978e-05,
1590
+ "loss": 0.1642,
1591
+ "step": 2260
1592
+ },
1593
+ {
1594
+ "epoch": 0.7264,
1595
+ "grad_norm": 4.681884765625,
1596
+ "learning_rate": 7.977767796990792e-05,
1597
+ "loss": 0.1613,
1598
+ "step": 2270
1599
+ },
1600
+ {
1601
+ "epoch": 0.7296,
1602
+ "grad_norm": 7.769372940063477,
1603
+ "learning_rate": 7.966539411632607e-05,
1604
+ "loss": 0.1544,
1605
+ "step": 2280
1606
+ },
1607
+ {
1608
+ "epoch": 0.7328,
1609
+ "grad_norm": 4.547751426696777,
1610
+ "learning_rate": 7.955311026274422e-05,
1611
+ "loss": 0.1636,
1612
+ "step": 2290
1613
+ },
1614
+ {
1615
+ "epoch": 0.736,
1616
+ "grad_norm": 8.214717864990234,
1617
+ "learning_rate": 7.944082640916236e-05,
1618
+ "loss": 0.1372,
1619
+ "step": 2300
1620
+ },
1621
+ {
1622
+ "epoch": 0.7392,
1623
+ "grad_norm": 7.887718677520752,
1624
+ "learning_rate": 7.932854255558051e-05,
1625
+ "loss": 0.158,
1626
+ "step": 2310
1627
+ },
1628
+ {
1629
+ "epoch": 0.7424,
1630
+ "grad_norm": 9.999999046325684,
1631
+ "learning_rate": 7.921625870199866e-05,
1632
+ "loss": 0.1611,
1633
+ "step": 2320
1634
+ },
1635
+ {
1636
+ "epoch": 0.7456,
1637
+ "grad_norm": 3.0139806270599365,
1638
+ "learning_rate": 7.910397484841681e-05,
1639
+ "loss": 0.1584,
1640
+ "step": 2330
1641
+ },
1642
+ {
1643
+ "epoch": 0.7488,
1644
+ "grad_norm": 5.308823585510254,
1645
+ "learning_rate": 7.899169099483495e-05,
1646
+ "loss": 0.1489,
1647
+ "step": 2340
1648
+ },
1649
+ {
1650
+ "epoch": 0.752,
1651
+ "grad_norm": 1.894464373588562,
1652
+ "learning_rate": 7.887940714125309e-05,
1653
+ "loss": 0.1335,
1654
+ "step": 2350
1655
+ },
1656
+ {
1657
+ "epoch": 0.7552,
1658
+ "grad_norm": 8.55656909942627,
1659
+ "learning_rate": 7.876712328767124e-05,
1660
+ "loss": 0.1363,
1661
+ "step": 2360
1662
+ },
1663
+ {
1664
+ "epoch": 0.7584,
1665
+ "grad_norm": 7.630896091461182,
1666
+ "learning_rate": 7.865483943408937e-05,
1667
+ "loss": 0.1398,
1668
+ "step": 2370
1669
+ },
1670
+ {
1671
+ "epoch": 0.7616,
1672
+ "grad_norm": 9.361071586608887,
1673
+ "learning_rate": 7.854255558050752e-05,
1674
+ "loss": 0.1307,
1675
+ "step": 2380
1676
+ },
1677
+ {
1678
+ "epoch": 0.7648,
1679
+ "grad_norm": 3.613555431365967,
1680
+ "learning_rate": 7.843027172692568e-05,
1681
+ "loss": 0.1461,
1682
+ "step": 2390
1683
+ },
1684
+ {
1685
+ "epoch": 0.768,
1686
+ "grad_norm": 4.020608901977539,
1687
+ "learning_rate": 7.831798787334381e-05,
1688
+ "loss": 0.1432,
1689
+ "step": 2400
1690
+ },
1691
+ {
1692
+ "epoch": 0.7712,
1693
+ "grad_norm": 6.401773452758789,
1694
+ "learning_rate": 7.820570401976196e-05,
1695
+ "loss": 0.1396,
1696
+ "step": 2410
1697
+ },
1698
+ {
1699
+ "epoch": 0.7744,
1700
+ "grad_norm": 6.332232475280762,
1701
+ "learning_rate": 7.809342016618011e-05,
1702
+ "loss": 0.1355,
1703
+ "step": 2420
1704
+ },
1705
+ {
1706
+ "epoch": 0.7776,
1707
+ "grad_norm": 2.399341344833374,
1708
+ "learning_rate": 7.798113631259825e-05,
1709
+ "loss": 0.1416,
1710
+ "step": 2430
1711
+ },
1712
+ {
1713
+ "epoch": 0.7808,
1714
+ "grad_norm": 5.8365654945373535,
1715
+ "learning_rate": 7.78688524590164e-05,
1716
+ "loss": 0.1265,
1717
+ "step": 2440
1718
+ },
1719
+ {
1720
+ "epoch": 0.784,
1721
+ "grad_norm": 10.0,
1722
+ "learning_rate": 7.775656860543454e-05,
1723
+ "loss": 0.6647,
1724
+ "step": 2450
1725
+ },
1726
+ {
1727
+ "epoch": 0.7872,
1728
+ "grad_norm": 5.435879230499268,
1729
+ "learning_rate": 7.764428475185269e-05,
1730
+ "loss": 0.1334,
1731
+ "step": 2460
1732
+ },
1733
+ {
1734
+ "epoch": 0.7904,
1735
+ "grad_norm": 10.0,
1736
+ "learning_rate": 7.753200089827083e-05,
1737
+ "loss": 0.1284,
1738
+ "step": 2470
1739
+ },
1740
+ {
1741
+ "epoch": 0.7936,
1742
+ "grad_norm": 7.202799320220947,
1743
+ "learning_rate": 7.741971704468898e-05,
1744
+ "loss": 0.1369,
1745
+ "step": 2480
1746
+ },
1747
+ {
1748
+ "epoch": 0.7968,
1749
+ "grad_norm": 2.0989317893981934,
1750
+ "learning_rate": 7.730743319110713e-05,
1751
+ "loss": 0.1105,
1752
+ "step": 2490
1753
+ },
1754
+ {
1755
+ "epoch": 0.8,
1756
+ "grad_norm": 4.924466609954834,
1757
+ "learning_rate": 7.719514933752526e-05,
1758
+ "loss": 0.1226,
1759
+ "step": 2500
1760
+ },
1761
+ {
1762
+ "epoch": 0.8032,
1763
+ "grad_norm": 7.978616714477539,
1764
+ "learning_rate": 7.708286548394342e-05,
1765
+ "loss": 0.1089,
1766
+ "step": 2510
1767
+ },
1768
+ {
1769
+ "epoch": 0.8064,
1770
+ "grad_norm": 4.150684356689453,
1771
+ "learning_rate": 7.697058163036157e-05,
1772
+ "loss": 0.1234,
1773
+ "step": 2520
1774
+ },
1775
+ {
1776
+ "epoch": 0.8096,
1777
+ "grad_norm": 4.818097114562988,
1778
+ "learning_rate": 7.68582977767797e-05,
1779
+ "loss": 0.1188,
1780
+ "step": 2530
1781
+ },
1782
+ {
1783
+ "epoch": 0.8128,
1784
+ "grad_norm": 2.5419697761535645,
1785
+ "learning_rate": 7.674601392319784e-05,
1786
+ "loss": 0.113,
1787
+ "step": 2540
1788
+ },
1789
+ {
1790
+ "epoch": 0.816,
1791
+ "grad_norm": 5.721562385559082,
1792
+ "learning_rate": 7.663373006961599e-05,
1793
+ "loss": 0.109,
1794
+ "step": 2550
1795
+ },
1796
+ {
1797
+ "epoch": 0.8192,
1798
+ "grad_norm": 2.7478086948394775,
1799
+ "learning_rate": 7.652144621603414e-05,
1800
+ "loss": 0.101,
1801
+ "step": 2560
1802
+ },
1803
+ {
1804
+ "epoch": 0.8224,
1805
+ "grad_norm": 9.692163467407227,
1806
+ "learning_rate": 7.640916236245228e-05,
1807
+ "loss": 0.1156,
1808
+ "step": 2570
1809
+ },
1810
+ {
1811
+ "epoch": 0.8256,
1812
+ "grad_norm": 6.791487693786621,
1813
+ "learning_rate": 7.629687850887043e-05,
1814
+ "loss": 0.12,
1815
+ "step": 2580
1816
+ },
1817
+ {
1818
+ "epoch": 0.8288,
1819
+ "grad_norm": 4.655740261077881,
1820
+ "learning_rate": 7.618459465528858e-05,
1821
+ "loss": 0.114,
1822
+ "step": 2590
1823
+ },
1824
+ {
1825
+ "epoch": 0.832,
1826
+ "grad_norm": 2.558154344558716,
1827
+ "learning_rate": 7.607231080170672e-05,
1828
+ "loss": 0.102,
1829
+ "step": 2600
1830
+ },
1831
+ {
1832
+ "epoch": 0.8352,
1833
+ "grad_norm": 5.348006725311279,
1834
+ "learning_rate": 7.596002694812487e-05,
1835
+ "loss": 0.156,
1836
+ "step": 2610
1837
+ },
1838
+ {
1839
+ "epoch": 0.8384,
1840
+ "grad_norm": 4.152245044708252,
1841
+ "learning_rate": 7.5847743094543e-05,
1842
+ "loss": 0.1256,
1843
+ "step": 2620
1844
+ },
1845
+ {
1846
+ "epoch": 0.8416,
1847
+ "grad_norm": 6.711794853210449,
1848
+ "learning_rate": 7.573545924096114e-05,
1849
+ "loss": 0.1184,
1850
+ "step": 2630
1851
+ },
1852
+ {
1853
+ "epoch": 0.8448,
1854
+ "grad_norm": 6.55480432510376,
1855
+ "learning_rate": 7.562317538737929e-05,
1856
+ "loss": 0.1253,
1857
+ "step": 2640
1858
+ },
1859
+ {
1860
+ "epoch": 0.848,
1861
+ "grad_norm": 6.035834312438965,
1862
+ "learning_rate": 7.551089153379744e-05,
1863
+ "loss": 0.125,
1864
+ "step": 2650
1865
+ },
1866
+ {
1867
+ "epoch": 0.8512,
1868
+ "grad_norm": 7.503954887390137,
1869
+ "learning_rate": 7.53986076802156e-05,
1870
+ "loss": 0.1068,
1871
+ "step": 2660
1872
+ },
1873
+ {
1874
+ "epoch": 0.8544,
1875
+ "grad_norm": 4.4410271644592285,
1876
+ "learning_rate": 7.528632382663373e-05,
1877
+ "loss": 0.1137,
1878
+ "step": 2670
1879
+ },
1880
+ {
1881
+ "epoch": 0.8576,
1882
+ "grad_norm": 4.127198696136475,
1883
+ "learning_rate": 7.517403997305188e-05,
1884
+ "loss": 0.1127,
1885
+ "step": 2680
1886
+ },
1887
+ {
1888
+ "epoch": 0.8608,
1889
+ "grad_norm": 3.0780539512634277,
1890
+ "learning_rate": 7.506175611947003e-05,
1891
+ "loss": 0.1009,
1892
+ "step": 2690
1893
+ },
1894
+ {
1895
+ "epoch": 0.864,
1896
+ "grad_norm": 8.409754753112793,
1897
+ "learning_rate": 7.494947226588817e-05,
1898
+ "loss": 0.1017,
1899
+ "step": 2700
1900
+ },
1901
+ {
1902
+ "epoch": 0.8672,
1903
+ "grad_norm": 4.118874549865723,
1904
+ "learning_rate": 7.483718841230631e-05,
1905
+ "loss": 0.1,
1906
+ "step": 2710
1907
+ },
1908
+ {
1909
+ "epoch": 0.8704,
1910
+ "grad_norm": 2.367293357849121,
1911
+ "learning_rate": 7.472490455872446e-05,
1912
+ "loss": 0.1019,
1913
+ "step": 2720
1914
+ },
1915
+ {
1916
+ "epoch": 0.8736,
1917
+ "grad_norm": 5.165258884429932,
1918
+ "learning_rate": 7.46126207051426e-05,
1919
+ "loss": 0.0891,
1920
+ "step": 2730
1921
+ },
1922
+ {
1923
+ "epoch": 0.8768,
1924
+ "grad_norm": 1.9673935174942017,
1925
+ "learning_rate": 7.450033685156075e-05,
1926
+ "loss": 0.0869,
1927
+ "step": 2740
1928
+ },
1929
+ {
1930
+ "epoch": 0.88,
1931
+ "grad_norm": 4.972908020019531,
1932
+ "learning_rate": 7.43880529979789e-05,
1933
+ "loss": 0.0894,
1934
+ "step": 2750
1935
+ },
1936
+ {
1937
+ "epoch": 0.8832,
1938
+ "grad_norm": 4.128866195678711,
1939
+ "learning_rate": 7.427576914439703e-05,
1940
+ "loss": 0.0888,
1941
+ "step": 2760
1942
+ },
1943
+ {
1944
+ "epoch": 0.8864,
1945
+ "grad_norm": 1.7406138181686401,
1946
+ "learning_rate": 7.416348529081518e-05,
1947
+ "loss": 0.0876,
1948
+ "step": 2770
1949
+ },
1950
+ {
1951
+ "epoch": 0.8896,
1952
+ "grad_norm": 1.7218992710113525,
1953
+ "learning_rate": 7.405120143723333e-05,
1954
+ "loss": 0.0925,
1955
+ "step": 2780
1956
+ },
1957
+ {
1958
+ "epoch": 0.8928,
1959
+ "grad_norm": 2.668508768081665,
1960
+ "learning_rate": 7.393891758365149e-05,
1961
+ "loss": 0.0872,
1962
+ "step": 2790
1963
+ },
1964
+ {
1965
+ "epoch": 0.896,
1966
+ "grad_norm": 5.266975402832031,
1967
+ "learning_rate": 7.382663373006962e-05,
1968
+ "loss": 0.083,
1969
+ "step": 2800
1970
+ },
1971
+ {
1972
+ "epoch": 0.8992,
1973
+ "grad_norm": 2.1134185791015625,
1974
+ "learning_rate": 7.371434987648776e-05,
1975
+ "loss": 0.0871,
1976
+ "step": 2810
1977
+ },
1978
+ {
1979
+ "epoch": 0.9024,
1980
+ "grad_norm": 4.195724010467529,
1981
+ "learning_rate": 7.360206602290591e-05,
1982
+ "loss": 0.0941,
1983
+ "step": 2820
1984
+ },
1985
+ {
1986
+ "epoch": 0.9056,
1987
+ "grad_norm": 2.4259421825408936,
1988
+ "learning_rate": 7.348978216932405e-05,
1989
+ "loss": 0.0937,
1990
+ "step": 2830
1991
+ },
1992
+ {
1993
+ "epoch": 0.9088,
1994
+ "grad_norm": 2.7671356201171875,
1995
+ "learning_rate": 7.33774983157422e-05,
1996
+ "loss": 0.095,
1997
+ "step": 2840
1998
+ },
1999
+ {
2000
+ "epoch": 0.912,
2001
+ "grad_norm": 6.370889663696289,
2002
+ "learning_rate": 7.326521446216035e-05,
2003
+ "loss": 0.0826,
2004
+ "step": 2850
2005
+ },
2006
+ {
2007
+ "epoch": 0.9152,
2008
+ "grad_norm": 6.082813739776611,
2009
+ "learning_rate": 7.315293060857849e-05,
2010
+ "loss": 0.0891,
2011
+ "step": 2860
2012
+ },
2013
+ {
2014
+ "epoch": 0.9184,
2015
+ "grad_norm": 4.761292934417725,
2016
+ "learning_rate": 7.304064675499664e-05,
2017
+ "loss": 0.0905,
2018
+ "step": 2870
2019
+ },
2020
+ {
2021
+ "epoch": 0.9216,
2022
+ "grad_norm": 3.1539108753204346,
2023
+ "learning_rate": 7.292836290141479e-05,
2024
+ "loss": 0.0836,
2025
+ "step": 2880
2026
+ },
2027
+ {
2028
+ "epoch": 0.9248,
2029
+ "grad_norm": 3.095581531524658,
2030
+ "learning_rate": 7.281607904783292e-05,
2031
+ "loss": 0.0782,
2032
+ "step": 2890
2033
+ },
2034
+ {
2035
+ "epoch": 0.928,
2036
+ "grad_norm": 2.6302435398101807,
2037
+ "learning_rate": 7.270379519425106e-05,
2038
+ "loss": 0.0844,
2039
+ "step": 2900
2040
+ },
2041
+ {
2042
+ "epoch": 0.9312,
2043
+ "grad_norm": 4.609825134277344,
2044
+ "learning_rate": 7.259151134066921e-05,
2045
+ "loss": 0.0773,
2046
+ "step": 2910
2047
+ },
2048
+ {
2049
+ "epoch": 0.9344,
2050
+ "grad_norm": 6.823300361633301,
2051
+ "learning_rate": 7.247922748708736e-05,
2052
+ "loss": 0.0811,
2053
+ "step": 2920
2054
+ },
2055
+ {
2056
+ "epoch": 0.9376,
2057
+ "grad_norm": 2.5662624835968018,
2058
+ "learning_rate": 7.23669436335055e-05,
2059
+ "loss": 0.0751,
2060
+ "step": 2930
2061
+ },
2062
+ {
2063
+ "epoch": 0.9408,
2064
+ "grad_norm": 1.9695119857788086,
2065
+ "learning_rate": 7.225465977992365e-05,
2066
+ "loss": 0.087,
2067
+ "step": 2940
2068
+ },
2069
+ {
2070
+ "epoch": 0.944,
2071
+ "grad_norm": 3.3225550651550293,
2072
+ "learning_rate": 7.21423759263418e-05,
2073
+ "loss": 0.0825,
2074
+ "step": 2950
2075
+ },
2076
+ {
2077
+ "epoch": 0.9472,
2078
+ "grad_norm": 3.849437713623047,
2079
+ "learning_rate": 7.203009207275994e-05,
2080
+ "loss": 0.0767,
2081
+ "step": 2960
2082
+ },
2083
+ {
2084
+ "epoch": 0.9504,
2085
+ "grad_norm": 1.750457525253296,
2086
+ "learning_rate": 7.191780821917809e-05,
2087
+ "loss": 0.0882,
2088
+ "step": 2970
2089
+ },
2090
+ {
2091
+ "epoch": 0.9536,
2092
+ "grad_norm": 6.477813243865967,
2093
+ "learning_rate": 7.180552436559623e-05,
2094
+ "loss": 0.0919,
2095
+ "step": 2980
2096
+ },
2097
+ {
2098
+ "epoch": 0.9568,
2099
+ "grad_norm": 1.4271601438522339,
2100
+ "learning_rate": 7.169324051201438e-05,
2101
+ "loss": 0.0804,
2102
+ "step": 2990
2103
+ },
2104
+ {
2105
+ "epoch": 0.96,
2106
+ "grad_norm": 7.061021327972412,
2107
+ "learning_rate": 7.158095665843251e-05,
2108
+ "loss": 0.0832,
2109
+ "step": 3000
2110
+ },
2111
+ {
2112
+ "epoch": 0.9632,
2113
+ "grad_norm": 2.1753170490264893,
2114
+ "learning_rate": 7.146867280485066e-05,
2115
+ "loss": 0.0741,
2116
+ "step": 3010
2117
+ },
2118
+ {
2119
+ "epoch": 0.9664,
2120
+ "grad_norm": 7.894692897796631,
2121
+ "learning_rate": 7.135638895126882e-05,
2122
+ "loss": 0.0723,
2123
+ "step": 3020
2124
+ },
2125
+ {
2126
+ "epoch": 0.9696,
2127
+ "grad_norm": 2.4842376708984375,
2128
+ "learning_rate": 7.124410509768695e-05,
2129
+ "loss": 0.0746,
2130
+ "step": 3030
2131
+ },
2132
+ {
2133
+ "epoch": 0.9728,
2134
+ "grad_norm": 4.693914413452148,
2135
+ "learning_rate": 7.11318212441051e-05,
2136
+ "loss": 0.0818,
2137
+ "step": 3040
2138
+ },
2139
+ {
2140
+ "epoch": 0.976,
2141
+ "grad_norm": 3.4993011951446533,
2142
+ "learning_rate": 7.101953739052325e-05,
2143
+ "loss": 0.0743,
2144
+ "step": 3050
2145
+ },
2146
+ {
2147
+ "epoch": 0.9792,
2148
+ "grad_norm": 2.4109108448028564,
2149
+ "learning_rate": 7.090725353694139e-05,
2150
+ "loss": 0.0698,
2151
+ "step": 3060
2152
+ },
2153
+ {
2154
+ "epoch": 0.9824,
2155
+ "grad_norm": 3.363265037536621,
2156
+ "learning_rate": 7.079496968335954e-05,
2157
+ "loss": 0.076,
2158
+ "step": 3070
2159
+ },
2160
+ {
2161
+ "epoch": 0.9856,
2162
+ "grad_norm": 4.7013959884643555,
2163
+ "learning_rate": 7.068268582977768e-05,
2164
+ "loss": 0.0801,
2165
+ "step": 3080
2166
+ },
2167
+ {
2168
+ "epoch": 0.9888,
2169
+ "grad_norm": 1.858520269393921,
2170
+ "learning_rate": 7.057040197619582e-05,
2171
+ "loss": 0.0691,
2172
+ "step": 3090
2173
+ },
2174
+ {
2175
+ "epoch": 0.992,
2176
+ "grad_norm": 2.71395206451416,
2177
+ "learning_rate": 7.045811812261397e-05,
2178
+ "loss": 0.0811,
2179
+ "step": 3100
2180
+ },
2181
+ {
2182
+ "epoch": 0.9952,
2183
+ "grad_norm": 3.254763603210449,
2184
+ "learning_rate": 7.034583426903212e-05,
2185
+ "loss": 0.0772,
2186
+ "step": 3110
2187
+ },
2188
+ {
2189
+ "epoch": 0.9984,
2190
+ "grad_norm": 6.519776821136475,
2191
+ "learning_rate": 7.023355041545027e-05,
2192
+ "loss": 0.0718,
2193
+ "step": 3120
2194
+ }
2195
+ ],
2196
+ "logging_steps": 10,
2197
+ "max_steps": 9375,
2198
+ "num_input_tokens_seen": 0,
2199
+ "num_train_epochs": 3,
2200
+ "save_steps": 500,
2201
+ "stateful_callbacks": {
2202
+ "TrainerControl": {
2203
+ "args": {
2204
+ "should_epoch_stop": false,
2205
+ "should_evaluate": false,
2206
+ "should_log": false,
2207
+ "should_save": true,
2208
+ "should_training_stop": false
2209
+ },
2210
+ "attributes": {}
2211
+ }
2212
+ },
2213
+ "total_flos": 0.0,
2214
+ "train_batch_size": 32,
2215
+ "trial_name": null,
2216
+ "trial_params": null
2217
+ }
checkpoint-3125/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:97555f8ce3aa7913ee05adca8d58969542dca6efa4c6dcd6a6ea25e10d7fbbd0
3
+ size 5304
checkpoint-3125/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-6250/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: gpt2-medium
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
checkpoint-6250/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": {
4
+ "base_model_class": "GPT2LMHeadModel",
5
+ "parent_library": "transformers.models.gpt2.modeling_gpt2"
6
+ },
7
+ "base_model_name_or_path": "gpt2-medium",
8
+ "bias": "none",
9
+ "fan_in_fan_out": true,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 128,
17
+ "lora_dropout": 0.0,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": null,
21
+ "peft_type": "LORA",
22
+ "r": 64,
23
+ "rank_pattern": {},
24
+ "revision": null,
25
+ "target_modules": [
26
+ "c_attn"
27
+ ],
28
+ "task_type": null,
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
checkpoint-6250/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:689c64ef188fa74751e49b80968470e493c5588180844da5342020e2265c2c8a
3
+ size 25172088
checkpoint-6250/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-6250/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:40b6d520a4dfbd55f460e5a668a9110172c1747f47a389e7f0b4e99302f3d2cf
3
+ size 50372538
checkpoint-6250/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:52fefebcb3a72d7a7a7ad505177d152a6c69b3050bea80f92945b4d318c2414f
3
+ size 14244
checkpoint-6250/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:54bf5bc35983da2516a319daa8db116d3e18d36fcecad8a541a6fed01b6c2f20
3
+ size 1064
checkpoint-6250/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<|endoftext|>",
4
+ "lstrip": false,
5
+ "normalized": true,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "<|endoftext|>",
11
+ "lstrip": false,
12
+ "normalized": true,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "<|endoftext|>",
17
+ "unk_token": {
18
+ "content": "<|endoftext|>",
19
+ "lstrip": false,
20
+ "normalized": true,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
checkpoint-6250/tokenizer_config.json ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "50256": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": true,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ }
13
+ },
14
+ "bos_token": "<|endoftext|>",
15
+ "clean_up_tokenization_spaces": false,
16
+ "eos_token": "<|endoftext|>",
17
+ "errors": "replace",
18
+ "model_max_length": 1024,
19
+ "pad_token": "<|endoftext|>",
20
+ "tokenizer_class": "GPT2Tokenizer",
21
+ "unk_token": "<|endoftext|>"
22
+ }
checkpoint-6250/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-6250/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:97555f8ce3aa7913ee05adca8d58969542dca6efa4c6dcd6a6ea25e10d7fbbd0
3
+ size 5304
checkpoint-6250/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-9375/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: gpt2-medium
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
checkpoint-9375/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": {
4
+ "base_model_class": "GPT2LMHeadModel",
5
+ "parent_library": "transformers.models.gpt2.modeling_gpt2"
6
+ },
7
+ "base_model_name_or_path": "gpt2-medium",
8
+ "bias": "none",
9
+ "fan_in_fan_out": true,
10
+ "inference_mode": true,
11
+ "init_lora_weights": true,
12
+ "layer_replication": null,
13
+ "layers_pattern": null,
14
+ "layers_to_transform": null,
15
+ "loftq_config": {},
16
+ "lora_alpha": 128,
17
+ "lora_dropout": 0.0,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": null,
21
+ "peft_type": "LORA",
22
+ "r": 64,
23
+ "rank_pattern": {},
24
+ "revision": null,
25
+ "target_modules": [
26
+ "c_attn"
27
+ ],
28
+ "task_type": null,
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
checkpoint-9375/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4d1652c7a003dd8627cd4a9648e12d63c6d4c984d8c61b0fca89d4f8de2daeaf
3
+ size 25172088
checkpoint-9375/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-9375/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bdbcab328afafac35d79fcaa42038bc7602d341850862f4f9908d9d0fa0e6547
3
+ size 50372538
checkpoint-9375/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:50fdfeef75a872ba1bc02c850c42b1db8abc27c7b8844c939df6c63695af50cd
3
+ size 14244
checkpoint-9375/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a17c6f8f90b7492d85e3ccb69e5e19d7c97f2aa89c2af5ae7acd1722212a18fd
3
+ size 1064
checkpoint-9375/special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<|endoftext|>",
4
+ "lstrip": false,
5
+ "normalized": true,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "<|endoftext|>",
11
+ "lstrip": false,
12
+ "normalized": true,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "<|endoftext|>",
17
+ "unk_token": {
18
+ "content": "<|endoftext|>",
19
+ "lstrip": false,
20
+ "normalized": true,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
checkpoint-9375/tokenizer_config.json ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "50256": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": true,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ }
13
+ },
14
+ "bos_token": "<|endoftext|>",
15
+ "clean_up_tokenization_spaces": false,
16
+ "eos_token": "<|endoftext|>",
17
+ "errors": "replace",
18
+ "model_max_length": 1024,
19
+ "pad_token": "<|endoftext|>",
20
+ "tokenizer_class": "GPT2Tokenizer",
21
+ "unk_token": "<|endoftext|>"
22
+ }
checkpoint-9375/trainer_state.json ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-9375/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:97555f8ce3aa7913ee05adca8d58969542dca6efa4c6dcd6a6ea25e10d7fbbd0
3
+ size 5304
checkpoint-9375/vocab.json ADDED
The diff for this file is too large to render. See raw diff
 
config.json ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "gpt2-medium",
3
+ "activation_function": "gelu_new",
4
+ "architectures": [
5
+ "GPT2LMHeadModel"
6
+ ],
7
+ "attn_pdrop": 0.1,
8
+ "bos_token_id": 50256,
9
+ "embd_pdrop": 0.1,
10
+ "eos_token_id": 50256,
11
+ "initializer_range": 0.02,
12
+ "layer_norm_epsilon": 1e-05,
13
+ "model_type": "gpt2",
14
+ "n_ctx": 1024,
15
+ "n_embd": 1024,
16
+ "n_head": 16,
17
+ "n_inner": null,
18
+ "n_layer": 24,
19
+ "n_positions": 1024,
20
+ "n_special": 0,
21
+ "predict_special_tokens": true,
22
+ "reorder_and_upcast_attn": false,
23
+ "resid_pdrop": 0.1,
24
+ "scale_attn_by_inverse_layer_idx": false,
25
+ "scale_attn_weights": true,
26
+ "summary_activation": null,
27
+ "summary_first_dropout": 0.1,
28
+ "summary_proj_to_labels": true,
29
+ "summary_type": "cls_index",
30
+ "summary_use_proj": true,
31
+ "task_specific_params": {
32
+ "text-generation": {
33
+ "do_sample": true,
34
+ "max_length": 50
35
+ }
36
+ },
37
+ "transformers_version": "4.45.2",
38
+ "use_cache": true,
39
+ "vocab_size": 50257
40
+ }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
special_tokens_map.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<|endoftext|>",
4
+ "lstrip": false,
5
+ "normalized": true,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "eos_token": {
10
+ "content": "<|endoftext|>",
11
+ "lstrip": false,
12
+ "normalized": true,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": "<|endoftext|>",
17
+ "unk_token": {
18
+ "content": "<|endoftext|>",
19
+ "lstrip": false,
20
+ "normalized": true,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ }
24
+ }
tokenizer_config.json ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "50256": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": true,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ }
13
+ },
14
+ "bos_token": "<|endoftext|>",
15
+ "clean_up_tokenization_spaces": false,
16
+ "eos_token": "<|endoftext|>",
17
+ "errors": "replace",
18
+ "model_max_length": 1024,
19
+ "pad_token": "<|endoftext|>",
20
+ "tokenizer_class": "GPT2Tokenizer",
21
+ "unk_token": "<|endoftext|>"
22
+ }
training_logs.csv ADDED
@@ -0,0 +1,939 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ step,training_loss,grad_norm
2
+ 10,25.0099,10.000000953674316
3
+ 20,21.1499,10.0
4
+ 30,19.6111,9.999999046325684
5
+ 40,22.3722,10.0
6
+ 50,20.1462,9.999999046325684
7
+ 60,20.4235,10.0
8
+ 70,20.7853,10.0
9
+ 80,19.5459,10.0
10
+ 90,18.4778,9.999999046325684
11
+ 100,16.2191,9.999999046325684
12
+ 110,18.5773,10.0
13
+ 120,15.9389,9.999999046325684
14
+ 130,15.6064,10.0
15
+ 140,15.6366,10.000000953674316
16
+ 150,16.7232,10.000000953674316
17
+ 160,13.2957,10.0
18
+ 170,13.3429,10.0
19
+ 180,13.3301,9.999999046325684
20
+ 190,15.1708,10.000000953674316
21
+ 200,14.8533,10.0
22
+ 210,11.6389,10.0
23
+ 220,12.2515,9.999999046325684
24
+ 230,12.6637,10.0
25
+ 240,10.6091,9.999999046325684
26
+ 250,10.9362,9.999999046325684
27
+ 260,12.4545,10.0
28
+ 270,11.5238,10.000000953674316
29
+ 280,10.8966,10.0
30
+ 290,10.5903,10.0
31
+ 300,10.4872,10.0
32
+ 310,9.9663,10.0
33
+ 320,9.4655,9.999999046325684
34
+ 330,10.487,10.0
35
+ 340,9.3626,10.000001907348633
36
+ 350,9.864,10.0
37
+ 360,8.8008,9.999999046325684
38
+ 370,9.7772,10.0
39
+ 380,8.7418,10.0
40
+ 390,9.1157,9.999999046325684
41
+ 400,8.1395,10.000000953674316
42
+ 410,8.8305,10.0
43
+ 420,9.2089,10.0
44
+ 430,8.5206,10.000000953674316
45
+ 440,8.8993,9.999999046325684
46
+ 450,8.8173,10.0
47
+ 460,8.3408,10.000000953674316
48
+ 470,7.5853,10.0
49
+ 480,7.4544,10.0
50
+ 490,8.0499,10.000000953674316
51
+ 500,8.2335,10.0
52
+ 510,7.0574,10.0
53
+ 520,6.8412,10.0
54
+ 530,7.1418,10.0
55
+ 540,7.1722,10.0
56
+ 550,6.7641,10.0
57
+ 560,6.3646,10.0
58
+ 570,6.3469,10.0
59
+ 580,6.38,10.0
60
+ 590,5.8154,10.000000953674316
61
+ 600,5.6794,10.000000953674316
62
+ 610,5.4415,9.999999046325684
63
+ 620,4.7814,10.0
64
+ 630,4.8304,10.000000953674316
65
+ 640,4.9017,10.0
66
+ 650,4.5826,10.0
67
+ 660,4.4032,10.0
68
+ 670,4.4789,10.0
69
+ 680,3.5318,10.000000953674316
70
+ 690,3.9803,10.000000953674316
71
+ 700,3.3411,10.0
72
+ 710,3.8421,10.0
73
+ 720,3.8598,10.000000953674316
74
+ 730,3.6175,9.999999046325684
75
+ 740,3.3833,9.999999046325684
76
+ 750,3.1501,10.0
77
+ 760,3.2144,10.0
78
+ 770,3.1372,10.0
79
+ 780,2.728,10.0
80
+ 790,2.7485,10.0
81
+ 800,2.7431,10.000000953674316
82
+ 810,2.534,10.0
83
+ 820,2.6129,10.0
84
+ 830,2.6607,10.0
85
+ 840,2.5158,9.999999046325684
86
+ 850,2.2633,9.999999046325684
87
+ 860,2.4407,10.0
88
+ 870,2.1584,9.999999046325684
89
+ 880,2.1552,10.0
90
+ 890,1.8968,10.000000953674316
91
+ 900,1.9182,9.999999046325684
92
+ 910,1.9413,10.0
93
+ 920,1.8959,10.0
94
+ 930,1.9225,10.0
95
+ 940,1.8802,10.0
96
+ 950,1.8896,9.999999046325684
97
+ 960,1.7142,10.0
98
+ 970,1.6888,10.0
99
+ 980,1.6177,10.0
100
+ 990,1.645,10.0
101
+ 1000,1.6792,10.0
102
+ 1010,1.8599,10.0
103
+ 1020,1.6779,10.0
104
+ 1030,1.4669,9.999999046325684
105
+ 1040,1.3649,10.0
106
+ 1050,1.3987,10.0
107
+ 1060,1.2421,9.999998092651367
108
+ 1070,1.3011,9.999998092651367
109
+ 1080,1.2287,9.999999046325684
110
+ 1090,1.1587,10.0
111
+ 1100,1.2415,10.0
112
+ 1110,1.1415,10.0
113
+ 1120,1.1941,9.999998092651367
114
+ 1130,1.1668,10.0
115
+ 1140,1.0887,10.000000953674316
116
+ 1150,1.0604,9.999998092651367
117
+ 1160,0.9446,9.999999046325684
118
+ 1170,0.9737,9.999999046325684
119
+ 1180,0.9654,10.0
120
+ 1190,1.0253,10.000000953674316
121
+ 1200,0.8597,9.999999046325684
122
+ 1210,0.8202,9.999998092651367
123
+ 1220,0.8386,9.999999046325684
124
+ 1230,0.8318,9.999999046325684
125
+ 1240,0.8571,10.0
126
+ 1250,0.8326,9.999999046325684
127
+ 1260,0.7655,9.999999046325684
128
+ 1270,0.747,10.0
129
+ 1280,0.8671,10.0
130
+ 1290,0.8758,9.999999046325684
131
+ 1300,0.8714,10.000000953674316
132
+ 1310,0.8022,9.999999046325684
133
+ 1320,0.7234,8.615378379821777
134
+ 1330,0.7416,10.0
135
+ 1340,0.6898,10.0
136
+ 1350,0.6261,9.999999046325684
137
+ 1360,0.6267,10.0
138
+ 1370,0.6171,9.999999046325684
139
+ 1380,0.5677,9.999998092651367
140
+ 1390,0.5227,9.999999046325684
141
+ 1400,0.5775,9.999999046325684
142
+ 1410,0.6166,9.999998092651367
143
+ 1420,0.6165,10.0
144
+ 1430,0.5849,9.999999046325684
145
+ 1440,0.6439,10.0
146
+ 1450,0.5886,9.999998092651367
147
+ 1460,0.5935,9.999999046325684
148
+ 1470,0.5868,10.0
149
+ 1480,0.5489,9.999998092651367
150
+ 1490,0.5106,10.0
151
+ 1500,0.4885,9.999999046325684
152
+ 1510,0.5323,9.999999046325684
153
+ 1520,0.4359,9.999999046325684
154
+ 1530,0.4789,7.423900604248047
155
+ 1540,0.4367,9.999998092651367
156
+ 1550,0.465,7.3594489097595215
157
+ 1560,0.4244,9.999998092651367
158
+ 1570,0.4311,10.0
159
+ 1580,0.4787,9.999999046325684
160
+ 1590,0.4777,9.999999046325684
161
+ 1600,0.469,10.0
162
+ 1610,0.4519,10.0
163
+ 1620,0.4084,9.999998092651367
164
+ 1630,0.3627,9.999998092651367
165
+ 1640,0.3742,8.502776145935059
166
+ 1650,0.3525,10.0
167
+ 1660,0.3889,9.999999046325684
168
+ 1670,0.5584,10.0
169
+ 1680,0.3988,9.999999046325684
170
+ 1690,0.3439,8.782861709594727
171
+ 1700,0.3265,8.174032211303711
172
+ 1710,0.329,4.737403392791748
173
+ 1720,0.3093,9.999999046325684
174
+ 1730,0.3119,10.0
175
+ 1740,0.3227,10.0
176
+ 1750,0.2979,9.882418632507324
177
+ 1760,0.2693,9.999998092651367
178
+ 1770,0.3187,9.999999046325684
179
+ 1780,0.291,9.999999046325684
180
+ 1790,0.2833,7.839264869689941
181
+ 1800,0.2525,4.611258029937744
182
+ 1810,0.2727,4.125186443328857
183
+ 1820,0.2718,9.999999046325684
184
+ 1830,0.2787,9.999999046325684
185
+ 1840,0.2903,4.507540225982666
186
+ 1850,0.2821,8.763723373413086
187
+ 1860,0.2469,6.04974365234375
188
+ 1870,0.2389,9.999998092651367
189
+ 1880,0.2749,10.0
190
+ 1890,0.2829,10.0
191
+ 1900,0.2725,9.99999713897705
192
+ 1910,0.2698,10.000001907348633
193
+ 1920,0.2678,9.999999046325684
194
+ 1930,0.2741,10.0
195
+ 1940,0.2475,10.0
196
+ 1950,0.2711,9.999999046325684
197
+ 1960,0.2592,10.0
198
+ 1970,0.2348,9.999999046325684
199
+ 1980,0.2185,7.087158679962158
200
+ 1990,0.2443,6.557620048522949
201
+ 2000,0.2012,9.999999046325684
202
+ 2010,0.1992,8.828990936279297
203
+ 2020,0.2005,9.999998092651367
204
+ 2030,0.2244,10.0
205
+ 2040,0.3351,10.0
206
+ 2050,0.3391,10.0
207
+ 2060,0.2319,9.999998092651367
208
+ 2070,0.2222,10.0
209
+ 2080,0.1829,8.043660163879395
210
+ 2090,0.1756,5.343007564544678
211
+ 2100,0.1959,3.530430316925049
212
+ 2110,0.178,9.999999046325684
213
+ 2120,0.1867,10.0
214
+ 2130,0.1832,8.584357261657715
215
+ 2140,0.1771,4.891357421875
216
+ 2150,0.1527,5.522593021392822
217
+ 2160,0.1769,9.386947631835938
218
+ 2170,0.1889,10.0
219
+ 2180,0.1827,9.999999046325684
220
+ 2190,0.2055,9.999999046325684
221
+ 2200,0.1802,9.999998092651367
222
+ 2210,0.1706,9.999999046325684
223
+ 2220,0.1604,3.970720052719116
224
+ 2230,0.1453,3.6069769859313965
225
+ 2240,0.1516,3.9357783794403076
226
+ 2250,0.1512,5.958951950073242
227
+ 2260,0.1642,9.320231437683105
228
+ 2270,0.1613,4.681884765625
229
+ 2280,0.1544,7.769372940063477
230
+ 2290,0.1636,4.547751426696777
231
+ 2300,0.1372,8.214717864990234
232
+ 2310,0.158,7.887718677520752
233
+ 2320,0.1611,9.999999046325684
234
+ 2330,0.1584,3.0139806270599365
235
+ 2340,0.1489,5.308823585510254
236
+ 2350,0.1335,1.894464373588562
237
+ 2360,0.1363,8.55656909942627
238
+ 2370,0.1398,7.630896091461182
239
+ 2380,0.1307,9.361071586608887
240
+ 2390,0.1461,3.613555431365967
241
+ 2400,0.1432,4.020608901977539
242
+ 2410,0.1396,6.401773452758789
243
+ 2420,0.1355,6.332232475280762
244
+ 2430,0.1416,2.399341344833374
245
+ 2440,0.1265,5.8365654945373535
246
+ 2450,0.6647,10.0
247
+ 2460,0.1334,5.435879230499268
248
+ 2470,0.1284,10.0
249
+ 2480,0.1369,7.202799320220947
250
+ 2490,0.1105,2.0989317893981934
251
+ 2500,0.1226,4.924466609954834
252
+ 2510,0.1089,7.978616714477539
253
+ 2520,0.1234,4.150684356689453
254
+ 2530,0.1188,4.818097114562988
255
+ 2540,0.113,2.5419697761535645
256
+ 2550,0.109,5.721562385559082
257
+ 2560,0.101,2.7478086948394775
258
+ 2570,0.1156,9.692163467407227
259
+ 2580,0.12,6.791487693786621
260
+ 2590,0.114,4.655740261077881
261
+ 2600,0.102,2.558154344558716
262
+ 2610,0.156,5.348006725311279
263
+ 2620,0.1256,4.152245044708252
264
+ 2630,0.1184,6.711794853210449
265
+ 2640,0.1253,6.55480432510376
266
+ 2650,0.125,6.035834312438965
267
+ 2660,0.1068,7.503954887390137
268
+ 2670,0.1137,4.4410271644592285
269
+ 2680,0.1127,4.127198696136475
270
+ 2690,0.1009,3.0780539512634277
271
+ 2700,0.1017,8.409754753112793
272
+ 2710,0.1,4.118874549865723
273
+ 2720,0.1019,2.367293357849121
274
+ 2730,0.0891,5.165258884429932
275
+ 2740,0.0869,1.9673935174942017
276
+ 2750,0.0894,4.972908020019531
277
+ 2760,0.0888,4.128866195678711
278
+ 2770,0.0876,1.7406138181686401
279
+ 2780,0.0925,1.7218992710113525
280
+ 2790,0.0872,2.668508768081665
281
+ 2800,0.083,5.266975402832031
282
+ 2810,0.0871,2.1134185791015625
283
+ 2820,0.0941,4.195724010467529
284
+ 2830,0.0937,2.4259421825408936
285
+ 2840,0.095,2.7671356201171875
286
+ 2850,0.0826,6.370889663696289
287
+ 2860,0.0891,6.082813739776611
288
+ 2870,0.0905,4.761292934417725
289
+ 2880,0.0836,3.1539108753204346
290
+ 2890,0.0782,3.095581531524658
291
+ 2900,0.0844,2.6302435398101807
292
+ 2910,0.0773,4.609825134277344
293
+ 2920,0.0811,6.823300361633301
294
+ 2930,0.0751,2.5662624835968018
295
+ 2940,0.087,1.9695119857788086
296
+ 2950,0.0825,3.3225550651550293
297
+ 2960,0.0767,3.849437713623047
298
+ 2970,0.0882,1.750457525253296
299
+ 2980,0.0919,6.477813243865967
300
+ 2990,0.0804,1.4271601438522339
301
+ 3000,0.0832,7.061021327972412
302
+ 3010,0.0741,2.1753170490264893
303
+ 3020,0.0723,7.894692897796631
304
+ 3030,0.0746,2.4842376708984375
305
+ 3040,0.0818,4.693914413452148
306
+ 3050,0.0743,3.4993011951446533
307
+ 3060,0.0698,2.4109108448028564
308
+ 3070,0.076,3.363265037536621
309
+ 3080,0.0801,4.7013959884643555
310
+ 3090,0.0691,1.858520269393921
311
+ 3100,0.0811,2.71395206451416
312
+ 3110,0.0772,3.254763603210449
313
+ 3120,0.0718,6.519776821136475
314
+ 3130,0.0746,1.91741144657135
315
+ 3140,0.071,1.5471233129501343
316
+ 3150,0.0646,3.8411548137664795
317
+ 3160,0.068,4.6282267570495605
318
+ 3170,0.0706,3.1158607006073
319
+ 3180,0.0711,4.9777913093566895
320
+ 3190,0.0649,2.6763927936553955
321
+ 3200,0.066,4.165836334228516
322
+ 3210,0.068,9.641294479370117
323
+ 3220,0.0695,2.3524587154388428
324
+ 3230,0.0869,3.930358648300171
325
+ 3240,0.0734,3.403099298477173
326
+ 3250,0.0729,4.471584796905518
327
+ 3260,0.0649,2.041577100753784
328
+ 3270,0.068,4.053502559661865
329
+ 3280,0.0693,1.712865948677063
330
+ 3290,0.073,8.817410469055176
331
+ 3300,0.0665,1.9689174890518188
332
+ 3310,0.0683,4.147378921508789
333
+ 3320,0.0635,3.4082727432250977
334
+ 3330,0.0587,1.8768893480300903
335
+ 3340,0.0628,1.7891249656677246
336
+ 3350,0.059,1.5056793689727783
337
+ 3360,0.0642,2.3811066150665283
338
+ 3370,0.0573,4.5819902420043945
339
+ 3380,0.0926,3.9442105293273926
340
+ 3390,0.0765,4.184739112854004
341
+ 3400,0.0657,2.208756446838379
342
+ 3410,0.0584,1.9726155996322632
343
+ 3420,0.0663,2.3560941219329834
344
+ 3430,0.0652,4.31378173828125
345
+ 3440,0.0619,5.586067199707031
346
+ 3450,0.0653,4.057238578796387
347
+ 3460,0.0647,2.5588834285736084
348
+ 3470,0.0604,3.098489761352539
349
+ 3480,0.0665,3.6659464836120605
350
+ 3490,0.059,2.530979633331299
351
+ 3500,0.062,4.6189374923706055
352
+ 3510,0.0573,2.125894784927368
353
+ 3520,0.0588,3.884368896484375
354
+ 3530,0.0648,4.213693141937256
355
+ 3540,0.0585,4.863856315612793
356
+ 3550,0.0584,2.9554522037506104
357
+ 3560,0.0611,1.8812214136123657
358
+ 3570,0.0591,2.52107572555542
359
+ 3580,0.0622,3.270277500152588
360
+ 3590,0.0586,2.0023467540740967
361
+ 3600,0.0517,2.0342307090759277
362
+ 3610,0.0568,3.3358206748962402
363
+ 3620,0.0509,1.158366322517395
364
+ 3630,0.0642,1.7512037754058838
365
+ 3640,0.0559,1.3442176580429077
366
+ 3650,0.0565,4.689185619354248
367
+ 3660,0.0575,3.3459503650665283
368
+ 3670,0.0534,2.5210814476013184
369
+ 3680,0.0562,1.4273737668991089
370
+ 3690,0.0531,3.007507562637329
371
+ 3700,0.0521,2.328012228012085
372
+ 3710,0.0586,3.815755844116211
373
+ 3720,0.0559,2.570431709289551
374
+ 3730,0.0555,2.9417104721069336
375
+ 3740,0.0515,1.5327764749526978
376
+ 3750,0.054,3.548718214035034
377
+ 3760,0.0552,1.7067848443984985
378
+ 3770,0.0459,1.4624521732330322
379
+ 3780,0.0459,4.673206329345703
380
+ 3790,0.0515,2.1773905754089355
381
+ 3800,0.0623,4.247639179229736
382
+ 3810,17.18,2.148364543914795
383
+ 3820,0.0535,3.752838134765625
384
+ 3830,0.0552,3.2757108211517334
385
+ 3840,0.0495,2.085975408554077
386
+ 3850,0.0468,1.4556792974472046
387
+ 3860,0.0583,1.6175802946090698
388
+ 3870,0.0486,1.6184957027435303
389
+ 3880,0.0778,9.999999046325684
390
+ 3890,0.0771,7.507689952850342
391
+ 3900,0.1067,4.089766502380371
392
+ 3910,0.069,2.4886679649353027
393
+ 3920,0.0643,3.568296432495117
394
+ 3930,0.0568,2.1102867126464844
395
+ 3940,0.0591,1.3482815027236938
396
+ 3950,0.0576,2.092593193054199
397
+ 3960,0.0484,2.106621503829956
398
+ 3970,0.0433,2.036658525466919
399
+ 3980,0.0449,1.402249813079834
400
+ 3990,0.0482,2.1640737056732178
401
+ 4000,0.0463,2.2044899463653564
402
+ 4010,0.0549,7.269384384155273
403
+ 4020,0.0522,3.0673646926879883
404
+ 4030,0.0471,5.095019340515137
405
+ 4040,0.0483,3.6901588439941406
406
+ 4050,0.0456,1.2914890050888062
407
+ 4060,0.0475,2.4384307861328125
408
+ 4070,0.0456,1.596550703048706
409
+ 4080,0.0517,1.6937170028686523
410
+ 4090,0.0437,1.587768316268921
411
+ 4100,0.0457,4.193778991699219
412
+ 4110,0.0479,2.494598865509033
413
+ 4120,0.0433,2.869279623031616
414
+ 4130,0.0519,4.543278217315674
415
+ 4140,0.0492,1.5083669424057007
416
+ 4150,0.0426,2.1934690475463867
417
+ 4160,0.0441,2.10366153717041
418
+ 4170,0.0437,1.6721271276474
419
+ 4180,0.0432,4.587328910827637
420
+ 4190,0.053,2.2152934074401855
421
+ 4200,0.05,3.132293224334717
422
+ 4210,0.0408,3.02851939201355
423
+ 4220,0.046,2.1754748821258545
424
+ 4230,0.0428,2.0088369846343994
425
+ 4240,0.0424,2.7489728927612305
426
+ 4250,0.0448,1.6788060665130615
427
+ 4260,0.041,2.4949731826782227
428
+ 4270,0.0441,1.9527579545974731
429
+ 4280,0.043,2.471604108810425
430
+ 4290,0.0562,4.944948196411133
431
+ 4300,0.0469,2.4510498046875
432
+ 4310,0.0428,1.1143766641616821
433
+ 4320,0.0448,1.719165325164795
434
+ 4330,0.0417,2.277461528778076
435
+ 4340,0.038,3.449477195739746
436
+ 4350,0.0396,2.189485549926758
437
+ 4360,0.0398,1.732558012008667
438
+ 4370,0.0433,2.732851266860962
439
+ 4380,0.0361,1.4708316326141357
440
+ 4390,0.0438,2.114934206008911
441
+ 4400,0.0421,4.473976135253906
442
+ 4410,0.0437,1.1676849126815796
443
+ 4420,0.0351,2.1100847721099854
444
+ 4430,0.0456,2.426988124847412
445
+ 4440,0.0381,3.200514078140259
446
+ 4450,0.0414,1.525909423828125
447
+ 4460,0.0407,1.2169736623764038
448
+ 4470,0.0476,4.590202808380127
449
+ 4480,0.052,1.4722408056259155
450
+ 4490,0.0459,1.351094126701355
451
+ 4500,0.0446,1.2844514846801758
452
+ 4510,0.0392,0.783967912197113
453
+ 4520,0.0407,2.0353965759277344
454
+ 4530,0.0381,1.3156319856643677
455
+ 4540,0.0353,1.4378070831298828
456
+ 4550,0.0348,3.0744736194610596
457
+ 4560,0.0402,1.6298600435256958
458
+ 4570,0.0365,2.6494648456573486
459
+ 4580,0.0363,1.653573751449585
460
+ 4590,0.0393,1.7645295858383179
461
+ 4600,0.0406,4.306888580322266
462
+ 4610,0.0358,3.1965126991271973
463
+ 4620,0.0396,1.2502505779266357
464
+ 4630,0.035,2.091470718383789
465
+ 4640,0.0428,1.1398119926452637
466
+ 4650,0.0353,2.7160258293151855
467
+ 4660,0.0415,0.9645196199417114
468
+ 4670,0.036,4.158140182495117
469
+ 4680,0.0376,1.1706950664520264
470
+ 4690,0.0374,1.1529676914215088
471
+ 4700,0.037,1.944616675376892
472
+ 4710,0.0376,1.7939577102661133
473
+ 4720,0.0345,2.588820695877075
474
+ 4730,0.0355,1.099802017211914
475
+ 4740,0.036,1.9600342512130737
476
+ 4750,0.0413,3.2066643238067627
477
+ 4760,0.036,4.0401811599731445
478
+ 4770,0.0366,1.673994541168213
479
+ 4780,0.0375,4.127200126647949
480
+ 4790,0.0364,2.1488308906555176
481
+ 4800,0.0366,3.2764744758605957
482
+ 4810,0.0387,4.183980941772461
483
+ 4820,0.0376,2.350937604904175
484
+ 4830,0.0378,1.4431155920028687
485
+ 4840,0.0352,2.455113172531128
486
+ 4850,0.0388,2.4375059604644775
487
+ 4860,0.0352,1.8249945640563965
488
+ 4870,0.0366,2.562242031097412
489
+ 4880,0.0381,1.7993731498718262
490
+ 4890,0.0342,1.6024712324142456
491
+ 4900,0.0355,1.0818573236465454
492
+ 4910,0.0381,0.9753634929656982
493
+ 4920,0.0341,1.9120144844055176
494
+ 4930,0.0377,2.293750762939453
495
+ 4940,0.0343,3.1085097789764404
496
+ 4950,0.036,1.3106160163879395
497
+ 4960,0.0341,2.5809476375579834
498
+ 4970,0.0306,1.423450231552124
499
+ 4980,0.0339,3.155231475830078
500
+ 4990,0.0369,1.6214268207550049
501
+ 5000,0.0398,3.8274025917053223
502
+ 5010,0.0347,3.3754544258117676
503
+ 5020,0.0335,2.3379604816436768
504
+ 5030,0.0327,1.3889174461364746
505
+ 5040,0.0362,2.985076427459717
506
+ 5050,0.0365,1.5555957555770874
507
+ 5060,0.0384,2.723813533782959
508
+ 5070,0.0336,1.3659981489181519
509
+ 5080,0.0307,3.0281941890716553
510
+ 5090,0.0326,1.122520089149475
511
+ 5100,0.0331,2.31559681892395
512
+ 5110,0.0375,1.262046217918396
513
+ 5120,0.0344,2.673083782196045
514
+ 5130,0.0434,5.857226371765137
515
+ 5140,0.0477,2.3795230388641357
516
+ 5150,0.0524,2.1502673625946045
517
+ 5160,0.0429,1.4233574867248535
518
+ 5170,0.0345,2.0955042839050293
519
+ 5180,0.0351,2.341566562652588
520
+ 5190,0.0344,3.160850763320923
521
+ 5200,0.0331,2.272794485092163
522
+ 5210,0.0335,1.2717911005020142
523
+ 5220,0.0319,2.4570579528808594
524
+ 5230,0.0343,1.8033403158187866
525
+ 5240,0.032,1.5098129510879517
526
+ 5250,0.0327,1.48603355884552
527
+ 5260,0.0353,1.4422051906585693
528
+ 5270,0.0321,1.18756103515625
529
+ 5280,0.0352,1.1758790016174316
530
+ 5290,0.03,1.2466790676116943
531
+ 5300,0.0314,1.9264726638793945
532
+ 5310,0.0328,1.9639238119125366
533
+ 5320,0.0347,2.070943832397461
534
+ 5330,0.0333,2.0837361812591553
535
+ 5340,0.0323,1.9007681608200073
536
+ 5350,0.0341,4.6805830001831055
537
+ 5360,0.0288,1.4064592123031616
538
+ 5370,0.0303,3.4108219146728516
539
+ 5380,0.0314,0.9329103827476501
540
+ 5390,0.0284,1.681719183921814
541
+ 5400,0.0299,0.932102382183075
542
+ 5410,0.0329,2.7038533687591553
543
+ 5420,0.0303,1.4268467426300049
544
+ 5430,0.0326,1.9577819108963013
545
+ 5440,0.0325,2.5221760272979736
546
+ 5450,0.0295,3.2790379524230957
547
+ 5460,0.0307,0.8850557208061218
548
+ 5470,0.0289,1.8326717615127563
549
+ 5480,0.0292,1.3088713884353638
550
+ 5490,0.0311,1.0117987394332886
551
+ 5500,0.0278,2.7869484424591064
552
+ 5510,0.0278,1.3128660917282104
553
+ 5520,0.03,1.1051273345947266
554
+ 5530,0.0306,1.3793776035308838
555
+ 5540,0.0299,2.992269515991211
556
+ 5550,0.0356,1.6625593900680542
557
+ 5560,0.0349,1.0821179151535034
558
+ 5570,0.0313,1.0884099006652832
559
+ 5580,0.0306,1.5417124032974243
560
+ 5590,0.0329,2.5081472396850586
561
+ 5600,0.0331,0.9784805178642273
562
+ 5610,0.0295,2.7062466144561768
563
+ 5620,0.0294,2.028097629547119
564
+ 5630,0.0282,0.9252501130104065
565
+ 5640,0.029,1.6614617109298706
566
+ 5650,0.0286,1.5624871253967285
567
+ 5660,0.0299,1.7454490661621094
568
+ 5670,0.0296,1.7463639974594116
569
+ 5680,0.0317,1.4736864566802979
570
+ 5690,0.0293,1.21503484249115
571
+ 5700,0.0305,3.489445209503174
572
+ 5710,0.03,1.21157705783844
573
+ 5720,0.0288,2.4874978065490723
574
+ 5730,0.0354,1.4586814641952515
575
+ 5740,0.0345,1.2466408014297485
576
+ 5750,0.0281,1.0634334087371826
577
+ 5760,0.0311,1.6378570795059204
578
+ 5770,0.0298,1.5089457035064697
579
+ 5780,0.029,2.608259677886963
580
+ 5790,0.0268,1.7564635276794434
581
+ 5800,0.0274,1.1659057140350342
582
+ 5810,0.0272,2.8701725006103516
583
+ 5820,0.0279,1.034717321395874
584
+ 5830,0.0307,1.3043538331985474
585
+ 5840,0.0258,2.0375423431396484
586
+ 5850,0.0308,2.1126816272735596
587
+ 5860,0.0282,1.7014706134796143
588
+ 5870,0.0284,2.7476634979248047
589
+ 5880,0.0242,1.6362510919570923
590
+ 5890,0.0361,1.3239845037460327
591
+ 5900,0.0277,1.4442349672317505
592
+ 5910,0.0258,1.9677876234054565
593
+ 5920,0.0298,2.842235803604126
594
+ 5930,0.0292,1.5647774934768677
595
+ 5940,0.0357,1.7668209075927734
596
+ 5950,0.0302,2.651283025741577
597
+ 5960,0.0304,5.3611040115356445
598
+ 5970,0.0284,5.584418773651123
599
+ 5980,0.0297,3.7711610794067383
600
+ 5990,0.0289,0.7803456783294678
601
+ 6000,0.0247,1.1393859386444092
602
+ 6010,0.0276,1.7076109647750854
603
+ 6020,0.0277,1.2361043691635132
604
+ 6030,0.0279,1.1116836071014404
605
+ 6040,0.0284,2.2229862213134766
606
+ 6050,0.0306,1.5508464574813843
607
+ 6060,0.0308,1.7325248718261719
608
+ 6070,0.0261,1.0399812459945679
609
+ 6080,0.0297,2.994081974029541
610
+ 6090,0.0276,2.2742340564727783
611
+ 6100,0.0277,1.2096333503723145
612
+ 6110,0.0289,1.3712992668151855
613
+ 6120,0.0273,1.6062151193618774
614
+ 6130,0.0297,1.5088088512420654
615
+ 6140,0.026,0.9999478459358215
616
+ 6150,0.0285,1.0416607856750488
617
+ 6160,0.0259,1.9191815853118896
618
+ 6170,0.0259,1.457220196723938
619
+ 6180,0.0264,1.0753467082977295
620
+ 6190,0.0258,2.804377317428589
621
+ 6200,0.0282,1.9763532876968384
622
+ 6210,0.0244,2.1442463397979736
623
+ 6220,0.0251,1.6756515502929688
624
+ 6230,0.0276,2.3364181518554688
625
+ 6240,0.0266,3.023191452026367
626
+ 6250,0.0273,2.4868950843811035
627
+ 6260,0.027,2.500319480895996
628
+ 6270,0.0248,1.7919338941574097
629
+ 6280,0.0342,0.9290552139282227
630
+ 6290,0.0262,1.057898759841919
631
+ 6300,0.0262,1.664808750152588
632
+ 6310,0.0265,2.4442942142486572
633
+ 6320,0.0255,2.3966939449310303
634
+ 6330,0.0263,2.9697370529174805
635
+ 6340,0.0256,2.686727285385132
636
+ 6350,0.0238,1.7658582925796509
637
+ 6360,0.0227,0.8644446730613708
638
+ 6370,0.0441,10.0
639
+ 6380,0.0367,2.123744249343872
640
+ 6390,0.0335,5.936791896820068
641
+ 6400,0.0298,2.3005146980285645
642
+ 6410,0.0288,1.058663010597229
643
+ 6420,0.028,2.2832794189453125
644
+ 6430,0.024,1.0518248081207275
645
+ 6440,0.0253,0.7201146483421326
646
+ 6450,0.0246,1.5872597694396973
647
+ 6460,0.0267,1.0472866296768188
648
+ 6470,0.0244,1.5414655208587646
649
+ 6480,0.0232,1.91981840133667
650
+ 6490,0.0247,0.8029799461364746
651
+ 6500,0.0254,1.7385778427124023
652
+ 6510,0.0257,1.1203155517578125
653
+ 6520,0.0223,0.8405721783638
654
+ 6530,0.0241,0.8406912088394165
655
+ 6540,0.0228,1.0132052898406982
656
+ 6550,0.0266,1.5743025541305542
657
+ 6560,0.0221,2.5406606197357178
658
+ 6570,0.0241,1.8731350898742676
659
+ 6580,0.0235,1.8953135013580322
660
+ 6590,0.03,1.2279338836669922
661
+ 6600,0.0238,2.3483939170837402
662
+ 6610,0.0284,1.5353964567184448
663
+ 6620,0.0254,0.7940895557403564
664
+ 6630,0.0268,0.8867064118385315
665
+ 6640,0.0229,0.6823979020118713
666
+ 6650,0.0221,0.9054269790649414
667
+ 6660,0.0242,0.844618558883667
668
+ 6670,0.0229,1.4453538656234741
669
+ 6680,0.0223,1.9151674509048462
670
+ 6690,0.0245,0.8978673219680786
671
+ 6700,0.0237,1.192948341369629
672
+ 6710,0.0233,0.9310412406921387
673
+ 6720,0.0236,3.681347608566284
674
+ 6730,0.0209,1.9511719942092896
675
+ 6740,0.0233,0.8533463478088379
676
+ 6750,0.024,1.8927245140075684
677
+ 6760,0.0254,1.9887471199035645
678
+ 6770,0.0233,0.9910705089569092
679
+ 6780,0.0276,0.9697316884994507
680
+ 6790,0.0221,1.3073784112930298
681
+ 6800,0.0258,2.332897663116455
682
+ 6810,0.024,2.5246870517730713
683
+ 6820,0.0225,0.9514437317848206
684
+ 6830,0.0265,0.9734804630279541
685
+ 6840,0.0225,0.7412808537483215
686
+ 6850,0.0218,0.6654082536697388
687
+ 6860,0.0239,1.154433250427246
688
+ 6870,0.0227,2.431039571762085
689
+ 6880,0.0203,0.7000795602798462
690
+ 6890,0.0235,0.9966208338737488
691
+ 6900,0.0224,0.5826752185821533
692
+ 6910,0.0196,1.576804280281067
693
+ 6920,0.0204,0.846698522567749
694
+ 6930,0.022,1.1780568361282349
695
+ 6940,0.0227,1.391042709350586
696
+ 6950,0.0218,0.8042160868644714
697
+ 6960,0.02,1.000321388244629
698
+ 6970,0.0216,0.9171059131622314
699
+ 6980,0.0213,1.0661230087280273
700
+ 6990,0.0204,1.4091787338256836
701
+ 7000,0.0225,1.5097310543060303
702
+ 7010,0.0217,2.1942641735076904
703
+ 7020,0.0225,2.1799325942993164
704
+ 7030,0.0235,0.8118078708648682
705
+ 7040,0.022,0.6434078216552734
706
+ 7050,0.0215,2.233530282974243
707
+ 7060,0.0234,2.489169120788574
708
+ 7070,0.022,1.5902799367904663
709
+ 7080,0.0255,2.1637775897979736
710
+ 7090,0.0235,0.90614914894104
711
+ 7100,0.0233,2.2505555152893066
712
+ 7110,0.022,1.0614933967590332
713
+ 7120,0.0189,1.5377411842346191
714
+ 7130,0.0217,2.9292163848876953
715
+ 7140,0.0194,0.55870121717453
716
+ 7150,0.025,2.509446859359741
717
+ 7160,0.0215,2.2066006660461426
718
+ 7170,0.0224,1.0167932510375977
719
+ 7180,0.0227,1.1303454637527466
720
+ 7190,0.0264,1.1977907419204712
721
+ 7200,0.0232,1.1619302034378052
722
+ 7210,0.0213,0.7383434772491455
723
+ 7220,0.0229,1.3148552179336548
724
+ 7230,0.0244,3.0743839740753174
725
+ 7240,0.0209,2.406111240386963
726
+ 7250,0.0283,1.536865472793579
727
+ 7260,0.0226,0.5282655954360962
728
+ 7270,0.021,1.2603291273117065
729
+ 7280,0.0207,0.9980093240737915
730
+ 7290,0.0238,1.0919678211212158
731
+ 7300,0.0202,0.9208861589431763
732
+ 7310,0.0204,1.6525688171386719
733
+ 7320,0.0192,1.4176781177520752
734
+ 7330,0.0206,1.4673593044281006
735
+ 7340,0.0218,0.8493990302085876
736
+ 7350,0.0191,1.3118574619293213
737
+ 7360,0.0194,0.7866161465644836
738
+ 7370,0.0228,0.8892452120780945
739
+ 7380,0.0219,2.4955861568450928
740
+ 7390,0.0204,1.814651608467102
741
+ 7400,0.0228,1.1132270097732544
742
+ 7410,0.0208,0.7917268872261047
743
+ 7420,0.0225,1.779470443725586
744
+ 7430,0.0209,1.540031909942627
745
+ 7440,0.0201,0.795350193977356
746
+ 7450,0.0203,1.4017839431762695
747
+ 7460,0.0223,1.2247642278671265
748
+ 7470,0.0218,1.8473584651947021
749
+ 7480,0.0228,1.563549518585205
750
+ 7490,0.0184,0.9918416142463684
751
+ 7500,0.02,0.7983741164207458
752
+ 7510,0.0189,1.003884196281433
753
+ 7520,0.0187,2.06343150138855
754
+ 7530,0.0209,0.8900611400604248
755
+ 7540,0.0209,1.086491346359253
756
+ 7550,0.025,1.247149109840393
757
+ 7560,0.0189,1.2688690423965454
758
+ 7570,0.0267,0.8303091526031494
759
+ 7580,0.0205,1.7538371086120605
760
+ 7590,0.0223,0.9375876188278198
761
+ 7600,0.0203,1.3351136445999146
762
+ 7610,0.0193,0.670791506767273
763
+ 7620,0.0207,0.6955625414848328
764
+ 7630,0.0197,0.8708732724189758
765
+ 7640,0.1552,2.0503456592559814
766
+ 7650,0.0256,2.0993776321411133
767
+ 7660,0.0259,1.001733660697937
768
+ 7670,0.0271,1.1097873449325562
769
+ 7680,0.0234,1.4637205600738525
770
+ 7690,0.0224,0.7054375410079956
771
+ 7700,0.0198,1.0400899648666382
772
+ 7710,0.0239,1.1329540014266968
773
+ 7720,0.0225,1.9706392288208008
774
+ 7730,0.0227,0.9307739734649658
775
+ 7740,0.0197,1.021101951599121
776
+ 7750,0.022,0.6976405382156372
777
+ 7760,0.0209,1.2085492610931396
778
+ 7770,0.0202,0.9504523277282715
779
+ 7780,0.0191,1.4022413492202759
780
+ 7790,0.0195,0.7028554677963257
781
+ 7800,0.024,0.8556867241859436
782
+ 7810,0.0206,1.331692099571228
783
+ 7820,0.3014,3.2675046920776367
784
+ 7830,0.0234,1.7758318185806274
785
+ 7840,0.0225,1.8547520637512207
786
+ 7850,0.0208,0.6967349648475647
787
+ 7860,0.0198,1.194005012512207
788
+ 7870,0.0201,1.7068527936935425
789
+ 7880,0.0239,1.449600100517273
790
+ 7890,0.0225,1.0100475549697876
791
+ 7900,0.0215,0.9704424142837524
792
+ 7910,0.0192,0.7141832113265991
793
+ 7920,0.02,1.8738646507263184
794
+ 7930,0.0205,0.9470159411430359
795
+ 7940,0.0193,1.2336801290512085
796
+ 7950,0.0202,0.9015800952911377
797
+ 7960,0.0234,0.7350621223449707
798
+ 7970,0.0207,1.2060322761535645
799
+ 7980,0.0188,0.6335831880569458
800
+ 7990,0.0195,1.0557260513305664
801
+ 8000,0.0182,0.5716488361358643
802
+ 8010,0.0204,0.75430828332901
803
+ 8020,0.0226,0.7589021921157837
804
+ 8030,0.0197,0.9131786227226257
805
+ 8040,0.02,0.7432297468185425
806
+ 8050,0.0182,0.7287900447845459
807
+ 8060,0.0201,0.7430145740509033
808
+ 8070,0.0188,0.5040020942687988
809
+ 8080,0.0171,0.6938813328742981
810
+ 8090,0.0201,0.7587171792984009
811
+ 8100,0.0196,1.0006415843963623
812
+ 8110,0.0179,0.6382442116737366
813
+ 8120,0.0177,0.9802420735359192
814
+ 8130,0.0201,1.5089691877365112
815
+ 8140,0.0205,0.8414797782897949
816
+ 8150,0.0209,0.9343305230140686
817
+ 8160,0.0194,0.7130104899406433
818
+ 8170,0.0187,1.5550020933151245
819
+ 8180,0.0208,1.134194254875183
820
+ 8190,0.0194,0.9144425392150879
821
+ 8200,0.0177,1.6265108585357666
822
+ 8210,0.0183,1.8325061798095703
823
+ 8220,0.0185,1.106653094291687
824
+ 8230,0.0186,1.0227482318878174
825
+ 8240,0.0182,0.8500052094459534
826
+ 8250,0.0182,0.670935332775116
827
+ 8260,0.0205,1.164656400680542
828
+ 8270,0.0182,1.3024622201919556
829
+ 8280,0.0232,0.7322014570236206
830
+ 8290,0.0183,0.7198416590690613
831
+ 8300,0.0184,0.5351381897926331
832
+ 8310,0.0224,0.6597144603729248
833
+ 8320,0.0183,0.9235522747039795
834
+ 8330,0.0176,0.5945689082145691
835
+ 8340,0.0165,0.6714538335800171
836
+ 8350,0.0184,0.5681155323982239
837
+ 8360,0.0176,1.2865463495254517
838
+ 8370,0.0205,0.675859808921814
839
+ 8380,0.0183,0.7957953810691833
840
+ 8390,0.0188,0.9204811453819275
841
+ 8400,0.0175,1.300011157989502
842
+ 8410,0.0199,1.3987044095993042
843
+ 8420,0.0213,0.7248627543449402
844
+ 8430,0.0173,0.7257712483406067
845
+ 8440,0.0188,0.7517357468605042
846
+ 8450,0.0172,1.4544386863708496
847
+ 8460,0.0184,0.8707684278488159
848
+ 8470,0.0193,0.6012953519821167
849
+ 8480,0.0198,0.9415525197982788
850
+ 8490,0.0179,1.2781232595443726
851
+ 8500,0.0165,0.6411517262458801
852
+ 8510,0.0214,1.3048300743103027
853
+ 8520,0.0164,1.0317035913467407
854
+ 8530,0.0191,1.280391812324524
855
+ 8540,0.0194,1.2745990753173828
856
+ 8550,0.0187,0.811211884021759
857
+ 8560,0.0189,1.224231481552124
858
+ 8570,0.018,1.0096673965454102
859
+ 8580,0.0198,0.8405938148498535
860
+ 8590,0.0199,1.4348673820495605
861
+ 8600,0.0189,1.1237190961837769
862
+ 8610,0.0176,0.7278895974159241
863
+ 8620,0.0192,1.0273234844207764
864
+ 8630,0.0207,0.7905086278915405
865
+ 8640,0.0188,1.2564754486083984
866
+ 8650,0.0193,1.3913291692733765
867
+ 8660,0.0185,1.0669301748275757
868
+ 8670,0.0197,0.7301857471466064
869
+ 8680,0.0188,1.1367110013961792
870
+ 8690,0.0181,0.8318895101547241
871
+ 8700,0.0185,0.9521366953849792
872
+ 8710,0.0174,0.5941877961158752
873
+ 8720,0.0178,0.6861777305603027
874
+ 8730,0.0178,0.40648457407951355
875
+ 8740,0.0188,1.452647089958191
876
+ 8750,0.019,1.1174592971801758
877
+ 8760,0.023,0.76162189245224
878
+ 8770,0.019,0.9453418850898743
879
+ 8780,0.017,0.779726505279541
880
+ 8790,0.0184,2.2095513343811035
881
+ 8800,0.0179,0.6634120941162109
882
+ 8810,0.0163,1.0645198822021484
883
+ 8820,0.0175,0.751386284828186
884
+ 8830,0.0186,1.3877284526824951
885
+ 8840,0.0171,0.6783541440963745
886
+ 8850,0.0188,1.2080283164978027
887
+ 8860,0.0192,1.290414810180664
888
+ 8870,0.016,1.0223037004470825
889
+ 8880,0.0172,0.7657661437988281
890
+ 8890,0.0166,1.068636178970337
891
+ 8900,0.0176,0.7494480013847351
892
+ 8910,0.0167,0.9242642521858215
893
+ 8920,0.0167,0.5937004089355469
894
+ 8930,0.0176,1.159949779510498
895
+ 8940,0.0167,0.9256805777549744
896
+ 8950,0.0163,0.529428243637085
897
+ 8960,0.0182,1.145539402961731
898
+ 8970,0.0167,0.6877376437187195
899
+ 8980,0.0189,0.8787598013877869
900
+ 8990,0.016,0.8161001205444336
901
+ 9000,0.0178,0.7280420660972595
902
+ 9010,0.0176,0.5738248229026794
903
+ 9020,0.0174,0.648565411567688
904
+ 9030,0.0173,0.8187539577484131
905
+ 9040,0.0186,0.7371270656585693
906
+ 9050,0.0179,0.6220325827598572
907
+ 9060,0.0163,0.532849907875061
908
+ 9070,0.0167,1.0468082427978516
909
+ 9080,0.0172,0.8014238476753235
910
+ 9090,0.0204,0.7104499936103821
911
+ 9100,0.0177,1.26918363571167
912
+ 9110,0.0167,0.806438684463501
913
+ 9120,0.0256,1.2076534032821655
914
+ 9130,0.0205,0.5213536024093628
915
+ 9140,0.0166,0.7805724740028381
916
+ 9150,0.019,0.7784114480018616
917
+ 9160,0.0175,0.6235218644142151
918
+ 9170,0.0154,0.7562257647514343
919
+ 9180,0.018,0.5506068468093872
920
+ 9190,0.0151,0.8118301630020142
921
+ 9200,0.0159,0.9710285067558289
922
+ 9210,0.0175,0.6396836042404175
923
+ 9220,0.0181,0.6802005171775818
924
+ 9230,0.0164,0.8104036450386047
925
+ 9240,0.0157,0.545315146446228
926
+ 9250,0.0179,0.5534526705741882
927
+ 9260,0.0173,0.5620812177658081
928
+ 9270,0.0212,0.6944151520729065
929
+ 9280,0.0185,0.7129794359207153
930
+ 9290,0.0171,0.5501587390899658
931
+ 9300,0.0172,0.4670201241970062
932
+ 9310,0.0176,0.6461374759674072
933
+ 9320,0.0177,0.7871281504631042
934
+ 9330,0.0162,0.6447378396987915
935
+ 9340,0.0168,0.6140932440757751
936
+ 9350,0.0186,0.5023877024650574
937
+ 9360,0.0182,0.5248384475708008
938
+ 9370,0.0176,0.608130156993866
939
+ 9375,nan,nan
vocab.json ADDED
The diff for this file is too large to render. See raw diff