Model save

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- medalpaca/medical_meadow_medqa
+model-index:
+- name: mistral-7b-instruct-v02
+  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/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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.6.0`
+```yaml
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+
+trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+datasets:
+  - path: medalpaca/medical_meadow_medqa
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.2
+output_dir: ./qlora-mistral-7b
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+adapter: qlora
+lora_model_dir:
+lora_r: 256
+lora_alpha: 128
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+wandb_project:
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 1
+micro_batch_size: 2
+num_epochs: 3
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 0.00002
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16:
+tf32: 
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps:
+evals_per_epoch: 4
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+  - full_shard
+  - auto_wrap
+fsdp_config:
+  fsdp_limit_all_gathers: true
+  fsdp_sync_module_states: true
+  fsdp_offload_params: true
+  fsdp_use_orig_params: false
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_transformer_layer_cls_to_wrap:
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_sharding_strategy: FULL_SHARD
+special_tokens:
+
+wandb_project: mistral-7b-instruct-v02
+wandb_entity: 
+wandb_watch:
+wandb_name: 
+wandb_log_model: 
+
+hub_model_id: neginashz/mistral-7b-instruct-v02
+hub_strategy: 
+early_stopping_patience:
+
+resume_from_checkpoint:
+auto_resume_from_checkpoints: true
+early_stopping_patience:
+
+```
+
+</details><br>
+
+# mistral-7b-instruct-v02
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the medalpaca/medical_meadow_medqa dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1324
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 8
+- total_eval_batch_size: 8
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 3
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.1395        | 0.2683 | 11   | 0.1455          |
+| 0.117         | 0.5366 | 22   | 0.1259          |
+| 0.1221        | 0.8049 | 33   | 0.1206          |
+| 0.1076        | 1.0488 | 44   | 0.1149          |
+| 0.0906        | 1.3171 | 55   | 0.1119          |
+| 0.093         | 1.5854 | 66   | 0.1201          |
+| 0.0868        | 1.8537 | 77   | 0.1121          |
+| 0.0634        | 2.0976 | 88   | 0.1146          |
+| 0.0464        | 2.3659 | 99   | 0.1297          |
+| 0.0574        | 2.6341 | 110  | 0.1329          |
+| 0.047         | 2.9024 | 121  | 0.1324          |
+
+
+### Framework versions
+
+- PEFT 0.14.0
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.21.0