End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert/distilbert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 49ed9bc4c55f01d46b2c12ab72ec9d62
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# 49ed9bc4c55f01d46b2c12ab72ec9d62
+
+This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the contemmcm/cls_mmlu dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.0766
+- Data Size: 1.0
+- Epoch Runtime: 15.4281
+- Accuracy: 0.2733
+- F1 Macro: 0.2685
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: constant
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
+| No log        | 0     | 0    | 1.3892          | 0         | 1.0008        | 0.2340   | 0.1558   |
+| No log        | 1     | 438  | 1.3942          | 0.0078    | 1.5112        | 0.2527   | 0.1246   |
+| No log        | 2     | 876  | 1.3893          | 0.0156    | 1.4385        | 0.2520   | 0.1319   |
+| No log        | 3     | 1314 | 1.3910          | 0.0312    | 1.8313        | 0.2540   | 0.1051   |
+| No log        | 4     | 1752 | 1.3910          | 0.0625    | 2.3392        | 0.2487   | 0.0996   |
+| 0.0777        | 5     | 2190 | 1.3923          | 0.125     | 3.0842        | 0.2706   | 0.1803   |
+| 0.1834        | 6     | 2628 | 1.3844          | 0.25      | 5.0158        | 0.2699   | 0.2066   |
+| 1.386         | 7     | 3066 | 1.3841          | 0.5       | 8.4317        | 0.2773   | 0.2081   |
+| 1.3674        | 8.0   | 3504 | 1.3887          | 1.0       | 15.7729       | 0.2793   | 0.2412   |
+| 1.2399        | 9.0   | 3942 | 1.4814          | 1.0       | 15.3051       | 0.2766   | 0.2609   |
+| 0.9979        | 10.0  | 4380 | 1.7245          | 1.0       | 15.2724       | 0.2806   | 0.2733   |
+| 0.7247        | 11.0  | 4818 | 2.0766          | 1.0       | 15.4281       | 0.2733   | 0.2685   |
+
+
+### Framework versions
+
+- Transformers 4.57.0
+- Pytorch 2.8.0+cu128
+- Datasets 4.3.0
+- Tokenizers 0.22.1

config.json

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+{
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "dtype": "float32",
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.57.0",
+  "vocab_size": 119547
+}

model.safetensors

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+size 541323528

special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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+size 5969