End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- medalpaca/medical_meadow_medqa
+model-index:
+- name: qwen2-ins-full-fsdp
+  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: Qwen/Qwen2.5-7B-Instruct
+trust_remote_code: true
+
+load_in_8bit: 
+load_in_4bit:
+strict: false
+
+datasets:
+  - path: medalpaca/medical_meadow_medqa
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.2
+output_dir: ./fulloutputs/out
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+
+wandb_project: full-ft-qwen
+wandb_entity: 
+wandb_watch:
+wandb_name: 
+wandb_log_model: 
+
+gradient_accumulation_steps: 1
+micro_batch_size: 1
+num_epochs: 3
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 0.00002
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 10
+xformers_attention:
+flash_attention: true
+
+warmup_steps:
+eval_steps: 100
+save_steps: 100
+debug:
+deepspeed: deepspeed_configs/zero2.json
+weight_decay: 0.05
+fsdp:
+fsdp_config:
+special_tokens:
+
+hub_model_id: neginashz/qwen2-ins-full-fsdp
+early_stopping_patience: 3
+
+```
+
+</details><br>
+
+# qwen2-ins-full-fsdp
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the medalpaca/medical_meadow_medqa dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1810
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 4
+- total_eval_batch_size: 4
+- 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: 6
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.0548        | 1.3889 | 100  | 0.1461          |
+| 0.0061        | 2.7778 | 200  | 0.1810          |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.21.0

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