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--- |
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base_model: NousResearch/Meta-Llama-3-8B-Instruct |
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library_name: peft |
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license: other |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/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: NousResearch/Meta-Llama-3-8B-Instruct |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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chat_template: llama3 |
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datasets: |
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- path: absolute-feedback-long.jsonl |
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type: chat_template |
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chat_template: llama3 |
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field_messages: messages |
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message_field_role: role |
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message_field_content: content |
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roles: |
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user: |
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- user |
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assistant: |
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- assistant |
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val_set_size: 0.01 |
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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: false |
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adapter: lora |
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lora_model_dir: |
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lora_r: 32 |
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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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wandb_project: fincode |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 32 |
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micro_batch_size: 12 |
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num_epochs: 3 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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s2_attention: |
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deepspeed: deepspeed_configs/zero1.json |
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warmup_steps: 20 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 3 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/guijinson/fincode/runs/9bh77pfv) |
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# outputs/lora-out |
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This model is a fine-tuned version of [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0461 |
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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: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 3072 |
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- total_eval_batch_size: 96 |
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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: 20 |
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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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| 1.8935 | 0.0311 | 1 | 1.8884 | |
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| 1.6965 | 0.2490 | 8 | 1.5971 | |
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| 1.3733 | 0.4981 | 16 | 1.3446 | |
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| 1.2466 | 0.7471 | 24 | 1.2463 | |
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| 1.1852 | 0.9961 | 32 | 1.1822 | |
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| 1.1444 | 1.2451 | 40 | 1.1379 | |
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| 1.0986 | 1.4942 | 48 | 1.1052 | |
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| 1.0774 | 1.7432 | 56 | 1.0816 | |
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| 1.065 | 1.9922 | 64 | 1.0657 | |
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| 1.055 | 2.2412 | 72 | 1.0551 | |
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| 1.0438 | 2.4903 | 80 | 1.0484 | |
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| 1.0394 | 2.7393 | 88 | 1.0463 | |
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| 1.0466 | 2.9883 | 96 | 1.0461 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
