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--- |
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library_name: peft |
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license: llama3.2 |
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base_model: unsloth/Llama-3.2-3B |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: e7a8531a-f667-43d7-96f2-07ed1b116e7e |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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adapter: lora |
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base_model: unsloth/Llama-3.2-3B |
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bf16: true |
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chat_template: llama3 |
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dataset_prepared_path: null |
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datasets: |
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- data_files: |
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- b10b004d99069455_train_data.json |
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ds_type: json |
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format: custom |
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path: /workspace/input_data/b10b004d99069455_train_data.json |
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type: |
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field_instruction: startphrase |
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field_output: gold-ending |
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format: '{instruction}' |
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no_input_format: '{instruction}' |
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system_format: '{system}' |
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system_prompt: '' |
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debug: null |
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device_map: |
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? '' |
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: 0,1,2,3,4,5,6,7 |
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early_stopping_patience: 2 |
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eval_max_new_tokens: 128 |
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eval_steps: 100 |
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eval_table_size: null |
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flash_attention: true |
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gradient_accumulation_steps: 8 |
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gradient_checkpointing: true |
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group_by_length: false |
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hub_model_id: Alphatao/e7a8531a-f667-43d7-96f2-07ed1b116e7e |
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hub_repo: null |
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hub_strategy: null |
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hub_token: null |
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learning_rate: 0.0002 |
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load_best_model_at_end: true |
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load_in_4bit: false |
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load_in_8bit: false |
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local_rank: null |
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logging_steps: 1 |
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lora_alpha: 32 |
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lora_dropout: 0.05 |
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lora_fan_in_fan_out: null |
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lora_model_dir: null |
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lora_r: 16 |
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lora_target_linear: true |
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lora_target_modules: |
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- q_proj |
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- k_proj |
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- v_proj |
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- o_proj |
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- down_proj |
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- up_proj |
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lr_scheduler: cosine |
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max_grad_norm: 1.0 |
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max_steps: 2346 |
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micro_batch_size: 4 |
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mlflow_experiment_name: /tmp/b10b004d99069455_train_data.json |
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model_type: AutoModelForCausalLM |
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num_epochs: 2 |
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optimizer: adamw_bnb_8bit |
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output_dir: miner_id_24 |
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pad_to_sequence_len: true |
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resume_from_checkpoint: null |
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s2_attention: null |
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sample_packing: false |
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save_steps: 100 |
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sequence_len: 2048 |
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strict: false |
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tf32: true |
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tokenizer_type: AutoTokenizer |
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train_on_inputs: false |
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trust_remote_code: true |
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val_set_size: 0.05 |
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wandb_entity: null |
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wandb_mode: online |
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wandb_name: 2d26c05a-cd41-4443-90b8-af6e34d0351b |
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wandb_project: Gradients-On-Demand |
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wandb_run: your_name |
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wandb_runid: 2d26c05a-cd41-4443-90b8-af6e34d0351b |
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warmup_steps: 10 |
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weight_decay: 0.0 |
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xformers_attention: null |
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``` |
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</details><br> |
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# e7a8531a-f667-43d7-96f2-07ed1b116e7e |
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This model is a fine-tuned version of [unsloth/Llama-3.2-3B](https://huggingface.co/unsloth/Llama-3.2-3B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2395 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- training_steps: 2346 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 4.4298 | 0.0004 | 1 | 4.2132 | |
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| 2.6515 | 0.0364 | 100 | 2.4191 | |
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| 2.224 | 0.0729 | 200 | 2.3802 | |
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| 2.7286 | 0.1093 | 300 | 2.3568 | |
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| 2.4288 | 0.1457 | 400 | 2.3433 | |
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| 2.2517 | 0.1822 | 500 | 2.3338 | |
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| 2.3638 | 0.2186 | 600 | 2.3226 | |
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| 2.4078 | 0.2550 | 700 | 2.3116 | |
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| 2.4365 | 0.2915 | 800 | 2.3066 | |
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| 2.3669 | 0.3279 | 900 | 2.3001 | |
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| 2.363 | 0.3643 | 1000 | 2.2917 | |
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| 2.2615 | 0.4008 | 1100 | 2.2847 | |
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| 2.3083 | 0.4372 | 1200 | 2.2774 | |
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| 2.1599 | 0.4736 | 1300 | 2.2743 | |
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| 2.1445 | 0.5101 | 1400 | 2.2687 | |
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| 2.3314 | 0.5465 | 1500 | 2.2618 | |
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| 2.2573 | 0.5829 | 1600 | 2.2566 | |
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| 2.4727 | 0.6194 | 1700 | 2.2512 | |
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| 2.1696 | 0.6558 | 1800 | 2.2482 | |
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| 2.3054 | 0.6922 | 1900 | 2.2447 | |
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| 2.312 | 0.7287 | 2000 | 2.2424 | |
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| 2.2064 | 0.7651 | 2100 | 2.2407 | |
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| 2.4036 | 0.8015 | 2200 | 2.2398 | |
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| 2.2385 | 0.8380 | 2300 | 2.2395 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.0 |
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- Pytorch 2.5.0+cu124 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
