| library_name: transformers | |
| license: mit | |
| base_model: BAAI/bge-small-en-v1.5 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: dl2_hw2 | |
| 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. --> | |
| # dl2_hw2 | |
| This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0818 | |
| - Precision: 0.8836 | |
| - Recall: 0.9139 | |
| - F1: 0.8985 | |
| - Accuracy: 0.9802 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - 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: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.0739 | 1.0 | 626 | 0.0923 | 0.8679 | 0.9072 | 0.8871 | 0.9780 | | |
| | 0.064 | 2.0 | 1252 | 0.0834 | 0.8774 | 0.9145 | 0.8956 | 0.9795 | | |
| | 0.0563 | 3.0 | 1878 | 0.0818 | 0.8836 | 0.9139 | 0.8985 | 0.9802 | | |
| ### Framework versions | |
| - Transformers 4.53.3 | |
| - Pytorch 2.6.0+cu124 | |
| - Datasets 4.1.1 | |
| - Tokenizers 0.21.2 | |