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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/Mixtral-8x7B-Instruct-v0.1 |
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model-index: |
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- name: empower-functions-more-tools |
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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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adapter: qlora |
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base_model: mistralai/Mixtral-8x7B-Instruct-v0.1 |
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bf16: true |
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chat_template: inst |
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dataset_prepared_path: last_run_prepared |
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datasets: |
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- conversation: mistral |
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path: ./data/with_function_response/function_not_used_training_small.jsonl |
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type: sharegpt |
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- conversation: mistral |
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path: ./data/with_function_response/more_functions/function_used_training_small.jsonl |
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type: sharegpt |
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debug: null |
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eval_max_new_tokens: 256 |
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eval_steps: 0.2 |
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eval_table_size: null |
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flash_attention: true |
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fp16: false |
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fsdp: null |
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fsdp_config: null |
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gradient_accumulation_steps: 4 |
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gradient_checkpointing: true |
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group_by_length: false |
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hub_model_id: liuylhf/empower-functions-more-tools |
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learning_rate: 0.0002 |
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load_in_4bit: true |
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load_in_8bit: false |
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logging_steps: 1 |
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lora_alpha: 64 |
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lora_dropout: 0.05 |
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lora_model_dir: null |
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lora_r: 32 |
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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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loss_watchdog_patience: 3 |
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loss_watchdog_threshold: 5.0 |
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lr_scheduler: cosine |
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micro_batch_size: 2 |
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model_config: |
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output_router_logits: true |
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model_type: AutoModelForCausalLM |
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num_epochs: 2 |
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optimizer: paged_adamw_8bit |
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output_dir: 2af0968cad514d6e9d5fb8448230e1c6/model |
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pad_to_sequence_len: true |
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sample_packing: true |
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save_steps: 0.1 |
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sequence_len: 4096 |
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strict: false |
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tf32: false |
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tokenizer_type: LlamaTokenizer |
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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_log_model: end |
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wandb_name: mixtral-instruct-lora-no-negative |
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wandb_project: function-call |
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warmup_steps: 10 |
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weight_decay: 0.0 |
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``` |
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</details><br> |
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# empower-functions-more-tools |
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0899 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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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: 10 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.8129 | 0.0 | 1 | 2.0522 | |
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| 0.1202 | 0.4 | 104 | 0.1054 | |
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| 0.1092 | 0.8 | 208 | 0.0976 | |
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| 0.0861 | 1.18 | 312 | 0.0938 | |
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| 0.0689 | 1.58 | 416 | 0.0908 | |
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| 0.0865 | 1.98 | 520 | 0.0899 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.0 |
