--- library_name: peft license: other base_model: Qwen/Qwen2.5-7B-Instruct tags: - llama-factory - lora - generated_from_trainer model-index: - name: Limo_qwen results: [] --- # Limo_qwen This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the Limo dataset. It achieves the following results on the evaluation set: - Loss: 0.7120 ## 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: 8e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 16 - total_train_batch_size: 64 - 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_ratio: 0.05 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.8842 | 1.0 | 12 | 0.8997 | | 0.8086 | 2.0 | 24 | 0.8223 | | 0.7502 | 3.0 | 36 | 0.7781 | | 0.7287 | 4.0 | 48 | 0.7514 | | 0.6899 | 5.0 | 60 | 0.7341 | | 0.6934 | 6.0 | 72 | 0.7228 | | 0.6727 | 7.0 | 84 | 0.7168 | | 0.69 | 8.0 | 96 | 0.7134 | | 0.6892 | 9.0 | 108 | 0.7124 | | 0.6735 | 10.0 | 120 | 0.7120 | ### Framework versions - PEFT 0.15.2 - Transformers 4.52.4 - Pytorch 2.8.0+cu129 - Datasets 3.6.0 - Tokenizers 0.21.4