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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- AiAF/Codename-75567-Pretrainin.jsonl |
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model-index: |
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- name: Pretrained-QLoRA-Codename-75567-V1 |
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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: `0.8.0.dev0` |
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```yaml |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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# optionally might have model_type or tokenizer_type |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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# Automatically upload checkpoint and final model to HF |
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hub_model_id: AiAF/Pretrained-QLoRA-Codename-75567-V1 |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: AiAF/Codename-75567-Pretrainin.jsonl |
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type: completion |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.05 |
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output_dir: ./outputs/qlora-out |
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save_total_limit: 10 |
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adapter: qlora |
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lora_model_dir: |
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lora_r: 256 |
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lora_alpha: 64 |
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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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sequence_len: 512 |
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sample_packing: true |
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pad_to_sequence_len: true |
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eval_sample_packing: false |
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wandb_project: "LLM-Pretraining" |
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wandb_watch: "all" |
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wandb_name: "QLoRA-Codename-75567-V1" |
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wandb_log_model: "false" |
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wandb_run_id: "QLoRA-Codename-75567-V1" |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 10 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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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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warmup_steps: 1 |
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evals_per_epoch: 5 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 1 |
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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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``` |
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</details><br> |
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# Pretrained-QLoRA-Codename-75567-V1 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the AiAF/Codename-75567-Pretrainin.jsonl dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6938 |
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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-06 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 2 |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.8916 | 0.3333 | 1 | 1.8880 | |
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| 2.017 | 0.6667 | 2 | 1.8847 | |
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| 1.9119 | 1.0 | 3 | 1.8795 | |
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| 1.9716 | 1.3333 | 4 | 1.8711 | |
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| 1.8532 | 1.6667 | 5 | 1.8601 | |
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| 1.9759 | 2.0 | 6 | 1.8488 | |
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| 1.856 | 2.3333 | 7 | 1.8357 | |
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| 1.8404 | 2.6667 | 8 | 1.8241 | |
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| 1.976 | 3.0 | 9 | 1.8131 | |
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| 1.8504 | 3.3333 | 10 | 1.8012 | |
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| 1.8574 | 3.6667 | 11 | 1.7860 | |
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| 1.8194 | 4.0 | 12 | 1.7749 | |
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| 1.8022 | 4.3333 | 13 | 1.7646 | |
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| 1.7632 | 4.6667 | 14 | 1.7525 | |
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| 1.8326 | 5.0 | 15 | 1.7440 | |
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| 1.7696 | 5.3333 | 16 | 1.7325 | |
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| 1.8039 | 5.6667 | 17 | 1.7257 | |
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| 1.7019 | 6.0 | 18 | 1.7164 | |
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| 1.7878 | 6.3333 | 19 | 1.7132 | |
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| 1.718 | 6.6667 | 20 | 1.7093 | |
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| 1.6994 | 7.0 | 21 | 1.7049 | |
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| 1.785 | 7.3333 | 22 | 1.6996 | |
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| 1.6659 | 7.6667 | 23 | 1.6977 | |
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| 1.7241 | 8.0 | 24 | 1.6970 | |
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| 1.7397 | 8.3333 | 25 | 1.6952 | |
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| 1.6894 | 8.6667 | 26 | 1.6934 | |
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| 1.723 | 9.0 | 27 | 1.6932 | |
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| 1.7999 | 9.3333 | 28 | 1.6927 | |
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| 1.6715 | 9.6667 | 29 | 1.6941 | |
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| 1.6696 | 10.0 | 30 | 1.6938 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
