See axolotl config
axolotl version: 0.4.1
adapter: lora
base_model: tiiuae/falcon-7b
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- /workspace/input_data/5fd36b5611485db4_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/5fd36b5611485db4_train_data.json
type:
field_input: scenario_x
field_instruction: prompt
field_output: response_a
format: '{instruction} {input}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
device_map: auto
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
evals_per_epoch: null
flash_attention: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: JoshMe1/a71f4136-c9d5-4ff7-a763-fa6c1a8e32cc
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_8bit: true
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
0: 130GB
max_steps: 200
micro_batch_size: 2
mixed_precision: bf16
mlflow_experiment_name: /tmp/5fd36b5611485db4_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
offload_folder: /workspace/offload/b5176f4e-f30d-407a-a306-2d297ebac569
optimizer: adamw_hf
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
saves_per_epoch: null
sequence_len: 2048
special_tokens:
pad_token: <|endoftext|>
strict: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: b5176f4e-f30d-407a-a306-2d297ebac569
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b5176f4e-f30d-407a-a306-2d297ebac569
warmup_steps: 200
weight_decay: 0.01
xformers_attention: null
a71f4136-c9d5-4ff7-a763-fa6c1a8e32cc
This model is a fine-tuned version of tiiuae/falcon-7b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3475
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- training_steps: 200
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0008 | 1 | 1.7491 |
| 5.5919 | 0.0828 | 100 | 1.4061 |
| 5.1961 | 0.1657 | 200 | 1.3475 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
tiiuae/falcon-7b