| --- |
| license: apache-2.0 |
| library_name: peft |
| tags: |
| - axolotl |
| - generated_from_trainer |
| base_model: mistralai/Mixtral-8x7B-Instruct-v0.1 |
| model-index: |
| - name: mixtral-pb-10e |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| [<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) |
| <details><summary>See axolotl config</summary> |
|
|
| axolotl version: `0.4.0` |
| ```yaml |
| base_model: mistralai/Mixtral-8x7B-Instruct-v0.1 |
| model_type: AutoModelForCausalLM |
| tokenizer_type: LlamaTokenizer |
| trust_remote_code: true |
| |
| load_in_8bit: false |
| load_in_4bit: true |
| strict: false |
| chat_template: inst |
| |
| datasets: |
| - path: ./data/pablo_processed.jsonl |
| type: sharegpt |
| conversation: mistral |
| # - path: ./data/tool_used_training.jsonl |
| # type: sharegpt |
| # conversation: mistral |
| # - path: ./data/tool_not_used_training.jsonl |
| # type: sharegpt |
| # conversation: mistral |
| # - path: ./data/no_tools_training.jsonl |
| # type: sharegpt |
| # conversation: mistral |
| |
| hub_model_id: dyang415/mixtral-pb-10e |
| |
| |
| dataset_prepared_path: last_run_prepared |
| val_set_size: 0.0 |
| output_dir: ../mixtral-pb-10e |
| |
| model_config: |
| output_router_logits: true |
| |
| adapter: qlora |
| lora_model_dir: |
| |
| sequence_len: 16384 |
| sample_packing: true |
| pad_to_sequence_len: true |
| |
| lora_r: 8 |
| lora_alpha: 16 |
| lora_dropout: 0.05 |
| lora_target_modules: |
| - q_proj |
| - k_proj |
| - v_proj |
| - o_proj |
| |
| |
| # wandb_project: function-call |
| # wandb_name: mixtral-instruct-lora--v1 |
| # wandb_log_model: end |
| # hub_model_id: dyang415/mixtral-lora-v0 |
| |
| |
| gradient_accumulation_steps: 2 |
| micro_batch_size: 1 |
| num_epochs: 10 |
| optimizer: paged_adamw_8bit |
| lr_scheduler: cosine |
| learning_rate: 0.0002 |
| |
| train_on_inputs: false |
| group_by_length: false |
| bf16: true |
| fp16: false |
| tf32: false |
| |
| gradient_checkpointing: true |
| logging_steps: 1 |
| flash_attention: true |
| |
| loss_watchdog_threshold: 5.0 |
| loss_watchdog_patience: 3 |
| |
| warmup_steps: 10 |
| evals_per_epoch: 4 |
| eval_table_size: |
| eval_max_new_tokens: 128 |
| saves_per_epoch: 1 |
| debug: |
| weight_decay: 0.0 |
| fsdp: |
| fsdp_config: |
| |
| ``` |
|
|
| </details><br> |
|
|
| # mixtral-pb-10e |
|
|
| 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. |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
|
|
| The following `bitsandbytes` quantization config was used during training: |
| - quant_method: QuantizationMethod.BITS_AND_BYTES |
| - load_in_8bit: False |
| - load_in_4bit: True |
| - llm_int8_threshold: 6.0 |
| - llm_int8_skip_modules: None |
| - llm_int8_enable_fp32_cpu_offload: False |
| - llm_int8_has_fp16_weight: False |
| - bnb_4bit_quant_type: nf4 |
| - bnb_4bit_use_double_quant: True |
| - bnb_4bit_compute_dtype: bfloat16 |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0002 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 4 |
| - total_eval_batch_size: 2 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 10 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.7.0 |
| - Transformers 4.37.0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.0 |
