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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- axolotl |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: hc-mistral-alpaca |
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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: `0.4.0` |
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```yaml |
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base_model: mistralai/Mistral-7B-v0.1 |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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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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lora_fan_in_fan_out: false |
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data_seed: 49 |
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seed: 49 |
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datasets: |
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- path: sample_data/alpaca_synth_queries.jsonl |
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type: sharegpt |
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conversation: alpaca |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.1 |
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output_dir: ./qlora-alpaca-out |
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hub_model_id: caldana/hc-mistral-alpaca |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 896 |
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sample_packing: false |
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pad_to_sequence_len: true |
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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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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: |
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wandb_entity: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 16 |
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eval_batch_size: 16 |
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num_epochs: 100 |
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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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max_grad_norm: 1.0 |
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adam_beta2: 0.95 |
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adam_epsilon: 0.00001 |
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save_total_limit: 12 |
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train_on_inputs: false |
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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: |
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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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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 20 |
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evals_per_epoch: 3 |
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eval_table_size: |
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eval_table_max_new_tokens: 128 |
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saves_per_epoch: 6 |
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debug: |
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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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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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save_safetensors: true |
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``` |
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</details><br> |
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# hc-mistral-alpaca |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3648 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 49 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.334 | 0.6667 | 1 | 1.2849 | |
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| 1.3476 | 1.3333 | 2 | 1.2780 | |
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| 1.2981 | 2.0 | 3 | 1.2487 | |
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| 1.3157 | 2.6667 | 4 | 1.1840 | |
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| 1.1757 | 3.3333 | 5 | 1.0690 | |
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| 1.1376 | 4.0 | 6 | 0.9086 | |
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| 0.9395 | 4.6667 | 7 | 0.7184 | |
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| 0.7385 | 5.3333 | 8 | 0.5617 | |
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| 0.5541 | 6.0 | 9 | 0.4307 | |
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| 0.4056 | 6.6667 | 10 | 0.3257 | |
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| 0.2791 | 7.3333 | 11 | 0.2866 | |
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| 0.2198 | 8.0 | 12 | 0.2453 | |
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| 0.1746 | 8.6667 | 13 | 0.2167 | |
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| 0.1582 | 9.3333 | 14 | 0.2104 | |
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| 0.1515 | 10.0 | 15 | 0.1699 | |
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| 0.1168 | 10.6667 | 16 | 0.1502 | |
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| 0.087 | 11.3333 | 17 | 0.1415 | |
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| 0.1 | 12.0 | 18 | 0.1574 | |
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| 0.0832 | 12.6667 | 19 | 0.1699 | |
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| 0.0765 | 13.3333 | 20 | 0.1601 | |
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| 0.0697 | 14.0 | 21 | 0.1544 | |
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| 0.0625 | 14.6667 | 22 | 0.1653 | |
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| 0.0583 | 15.3333 | 23 | 0.1628 | |
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| 0.047 | 16.0 | 24 | 0.1463 | |
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| 0.0366 | 16.6667 | 25 | 0.1637 | |
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| 0.0342 | 17.3333 | 26 | 0.2020 | |
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| 0.0398 | 18.0 | 27 | 0.1801 | |
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| 0.0319 | 18.6667 | 28 | 0.1835 | |
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| 0.0229 | 19.3333 | 29 | 0.1957 | |
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| 0.0286 | 20.0 | 30 | 0.2024 | |
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| 0.0166 | 20.6667 | 31 | 0.2519 | |
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| 0.0184 | 21.3333 | 32 | 0.2699 | |
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| 0.0129 | 22.0 | 33 | 0.2813 | |
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| 0.0109 | 22.6667 | 34 | 0.2950 | |
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| 0.0105 | 23.3333 | 35 | 0.3037 | |
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| 0.0111 | 24.0 | 36 | 0.3161 | |
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| 0.0071 | 24.6667 | 37 | 0.3310 | |
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| 0.0115 | 25.3333 | 38 | 0.3375 | |
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| 0.0051 | 26.0 | 39 | 0.3456 | |
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| 0.004 | 26.6667 | 40 | 0.3488 | |
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| 0.0077 | 27.3333 | 41 | 0.3599 | |
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| 0.0028 | 28.0 | 42 | 0.3706 | |
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| 0.0021 | 28.6667 | 43 | 0.3737 | |
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| 0.002 | 29.3333 | 44 | 0.3729 | |
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| 0.0017 | 30.0 | 45 | 0.3742 | |
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| 0.0013 | 30.6667 | 46 | 0.3757 | |
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| 0.0004 | 31.3333 | 47 | 0.3755 | |
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| 0.0006 | 32.0 | 48 | 0.3764 | |
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| 0.0002 | 32.6667 | 49 | 0.3750 | |
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| 0.0011 | 33.3333 | 50 | 0.3646 | |
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| 0.0005 | 34.0 | 51 | 0.3586 | |
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| 0.0013 | 34.6667 | 52 | 0.3617 | |
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| 0.0005 | 35.3333 | 53 | 0.3638 | |
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| 0.0011 | 36.0 | 54 | 0.3657 | |
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| 0.0003 | 36.6667 | 55 | 0.3710 | |
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| 0.0002 | 37.3333 | 56 | 0.3711 | |
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| 0.0004 | 38.0 | 57 | 0.3736 | |
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| 0.0003 | 38.6667 | 58 | 0.3784 | |
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| 0.0001 | 39.3333 | 59 | 0.3795 | |
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| 0.0007 | 40.0 | 60 | 0.3737 | |
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| 0.0001 | 40.6667 | 61 | 0.3730 | |
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| 0.0003 | 41.3333 | 62 | 0.3729 | |
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| 0.0002 | 42.0 | 63 | 0.3714 | |
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| 0.0001 | 42.6667 | 64 | 0.3698 | |
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| 0.0001 | 43.3333 | 65 | 0.3704 | |
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| 0.0001 | 44.0 | 66 | 0.3704 | |
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| 0.0001 | 44.6667 | 67 | 0.3705 | |
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| 0.0001 | 45.3333 | 68 | 0.3655 | |
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| 0.0002 | 46.0 | 69 | 0.3672 | |
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| 0.0002 | 46.6667 | 70 | 0.3682 | |
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| 0.0002 | 47.3333 | 71 | 0.3656 | |
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| 0.0001 | 48.0 | 72 | 0.3663 | |
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| 0.0001 | 48.6667 | 73 | 0.3668 | |
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| 0.0001 | 49.3333 | 74 | 0.3673 | |
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| 0.0001 | 50.0 | 75 | 0.3638 | |
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| 0.0001 | 50.6667 | 76 | 0.3640 | |
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| 0.0001 | 51.3333 | 77 | 0.3643 | |
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| 0.0001 | 52.0 | 78 | 0.3640 | |
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| 0.0001 | 52.6667 | 79 | 0.3648 | |
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| 0.0001 | 53.3333 | 80 | 0.3629 | |
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| 0.0001 | 54.0 | 81 | 0.3648 | |
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| 0.0001 | 54.6667 | 82 | 0.3617 | |
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| 0.0001 | 55.3333 | 83 | 0.3632 | |
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| 0.0001 | 56.0 | 84 | 0.3650 | |
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| 0.0001 | 56.6667 | 85 | 0.3636 | |
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| 0.0001 | 57.3333 | 86 | 0.3633 | |
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| 0.0001 | 58.0 | 87 | 0.3673 | |
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| 0.0001 | 58.6667 | 88 | 0.3663 | |
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| 0.0001 | 59.3333 | 89 | 0.3618 | |
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| 0.0001 | 60.0 | 90 | 0.3635 | |
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| 0.0001 | 60.6667 | 91 | 0.3605 | |
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| 0.0001 | 61.3333 | 92 | 0.3654 | |
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| 0.0001 | 62.0 | 93 | 0.3647 | |
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| 0.0001 | 62.6667 | 94 | 0.3586 | |
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| 0.0001 | 63.3333 | 95 | 0.3601 | |
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| 0.0001 | 64.0 | 96 | 0.3631 | |
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| 0.0001 | 64.6667 | 97 | 0.3629 | |
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| 0.0001 | 65.3333 | 98 | 0.3652 | |
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| 0.0001 | 66.0 | 99 | 0.3645 | |
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| 0.0001 | 66.6667 | 100 | 0.3648 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
