--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B-Instruct tags: - generated_from_trainer model-index: - name: qwen_lora results: [] --- # qwen_lora This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0622 - Mse: 0.0622 - Mae: 0.1968 - R Squared: 0.3060 ## 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: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.01 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R Squared | |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:| | 0.0875 | 0.3115 | 100 | 0.0854 | 0.0854 | 0.2351 | 0.0471 | | 0.0786 | 0.6231 | 200 | 0.0741 | 0.0741 | 0.2186 | 0.1735 | | 0.0709 | 0.9346 | 300 | 0.0716 | 0.0716 | 0.2193 | 0.2018 | | 0.0675 | 1.2461 | 400 | 0.0735 | 0.0735 | 0.2106 | 0.1803 | | 0.0681 | 1.5576 | 500 | 0.0710 | 0.0710 | 0.2076 | 0.2081 | | 0.0627 | 1.8692 | 600 | 0.0675 | 0.0675 | 0.2059 | 0.2468 | | 0.0628 | 2.1807 | 700 | 0.0657 | 0.0657 | 0.2031 | 0.2677 | | 0.0591 | 2.4922 | 800 | 0.0646 | 0.0646 | 0.2033 | 0.2799 | | 0.06 | 2.8037 | 900 | 0.0660 | 0.0660 | 0.2007 | 0.2638 | | 0.0553 | 3.1153 | 1000 | 0.0633 | 0.0633 | 0.2012 | 0.2944 | | 0.0612 | 3.4268 | 1100 | 0.0654 | 0.0654 | 0.2078 | 0.2711 | | 0.0542 | 3.7383 | 1200 | 0.0627 | 0.0627 | 0.1987 | 0.3009 | | 0.0529 | 4.0498 | 1300 | 0.0623 | 0.0623 | 0.1970 | 0.3049 | | 0.0546 | 4.3614 | 1400 | 0.0624 | 0.0624 | 0.1962 | 0.3044 | | 0.0535 | 4.6729 | 1500 | 0.0623 | 0.0623 | 0.1972 | 0.3055 | | 0.0536 | 4.9844 | 1600 | 0.0622 | 0.0622 | 0.1968 | 0.3060 | ### Framework versions - PEFT 0.13.2 - Transformers 4.45.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3