--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: Qwen/Qwen2-7B metrics: - accuracy model-index: - name: QWEN_with_time results: [] --- # QWEN_with_time This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3495 - Balanced Accuracy: 0.8801 - Accuracy: 0.8801 - Micro F1: 0.8801 - Macro F1: 0.8800 - Weighted F1: 0.8800 - Classification Report: precision recall f1-score support 0 0.89 0.87 0.88 386 1 0.87 0.89 0.88 381 accuracy 0.88 767 macro avg 0.88 0.88 0.88 767 weighted avg 0.88 0.88 0.88 767 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy | Micro F1 | Macro F1 | Weighted F1 | Classification Report | |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:|:--------:|:--------:|:-----------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| | 0.6244 | 1.0 | 384 | 0.4657 | 0.8336 | 0.8331 | 0.8331 | 0.8323 | 0.8322 | precision recall f1-score support 0 0.89 0.76 0.82 386 1 0.79 0.91 0.84 381 accuracy 0.83 767 macro avg 0.84 0.83 0.83 767 weighted avg 0.84 0.83 0.83 767 | | 0.3513 | 2.0 | 768 | 0.4065 | 0.8639 | 0.8644 | 0.8644 | 0.8634 | 0.8635 | precision recall f1-score support 0 0.82 0.94 0.88 386 1 0.93 0.78 0.85 381 accuracy 0.86 767 macro avg 0.87 0.86 0.86 767 weighted avg 0.87 0.86 0.86 767 | | 0.2858 | 3.0 | 1152 | 0.3495 | 0.8801 | 0.8801 | 0.8801 | 0.8800 | 0.8800 | precision recall f1-score support 0 0.89 0.87 0.88 386 1 0.87 0.89 0.88 381 accuracy 0.88 767 macro avg 0.88 0.88 0.88 767 weighted avg 0.88 0.88 0.88 767 | ### Framework versions - PEFT 0.11.1 - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1