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--- |
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base_model: Qwen/Qwen2.5-14B-Instruct |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: outputs/lora-out |
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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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base_model: Qwen/Qwen2.5-14B-Instruct |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: output.jsonl |
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type: |
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field_instruction: instruction |
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field_input: input |
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field_output: output |
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format: "<|im_start|>system\n{instruction}<|im_end|>\n<|im_start|>user\n{input}<|im_end|>\n<|im_start|>assistant\n" |
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special_tokens: |
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bos_token: |
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eos_token: "<|im_end|>" |
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pad_token: "<|endoftext|>" |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./outputs/lora-out |
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sequence_len: 4096 |
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sample_packing: false |
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pad_to_sequence_len: true |
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adapter: lora |
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lora_model_dir: |
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lora_r: 8 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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wandb_project: mssong_axolotl |
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wandb_entity: mssong |
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wandb_watch: |
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wandb_run_id: |
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wandb_log_model: |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 1 |
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num_epochs: 3 |
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optimizer: |
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lr_scheduler: cosine |
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learning_rate: 0.00005 |
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train_on_inputs: |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: 3 |
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local_rank: |
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logging_steps: 10 |
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xformers_attention: |
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flash_attention: true |
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#warmup_ratio: 0.02 |
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warmup_steps: 100 |
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eval_steps: 100 |
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save_steps: 500 |
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save_total_limit: 2 |
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eval_sample_packing: |
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debug: |
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deepspeed: |
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weight_decay: 0.1 |
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fsdp: |
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fsdp_config: |
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trust_remote_code: true |
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``` |
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</details><br> |
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# outputs/lora-out |
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This model is a fine-tuned version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0405 |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 4 |
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- total_eval_batch_size: 2 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| No log | 0.0035 | 1 | 0.6979 | |
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| 0.046 | 0.3515 | 100 | 0.0793 | |
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| 0.0259 | 0.7030 | 200 | 0.0519 | |
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| 0.0242 | 1.0545 | 300 | 0.0447 | |
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| 0.0194 | 1.4060 | 400 | 0.0435 | |
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| 0.016 | 1.7575 | 500 | 0.0427 | |
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| 0.0097 | 2.1090 | 600 | 0.0392 | |
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| 0.0179 | 2.4605 | 700 | 0.0410 | |
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| 0.0081 | 2.8120 | 800 | 0.0405 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.45.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.0 |
