--- library_name: peft license: other base_model: Qwen/Qwen2.5-7B tags: - base_model:adapter:Qwen/Qwen2.5-7B - llama-factory - lora - transformers pipeline_tag: text-generation model-index: - name: qwen7b_lora_sft_8gpu_s13 results: [] --- # qwen7b_lora_sft_8gpu_s13 This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the assimilation_strict_json_v2 dataset. It achieves the following results on the evaluation set: - Loss: 0.1527 ## 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: 0.0001 - train_batch_size: 8 - eval_batch_size: 4 - seed: 13 - distributed_type: multi-GPU - num_devices: 8 - total_train_batch_size: 64 - total_eval_batch_size: 32 - optimizer: Use OptimizerNames.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: 0.05 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.1567 | 0.6667 | 50 | 0.1561 | | 0.1533 | 1.3333 | 100 | 0.1532 | | 0.1528 | 2.0 | 150 | 0.1527 | | 0.1527 | 2.6667 | 200 | 0.1527 | | 0.1527 | 3.0 | 225 | 0.1527 | ### Framework versions - PEFT 0.18.1 - Transformers 5.6.0 - Pytorch 2.7.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2