| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: Paper-Matcher-bert |
| 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. --> |
|
|
| # Paper-Matcher-bert |
|
|
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5883 |
| - Accuracy: 0.87 |
| - Macro F1: 0.8699 |
|
|
| ## 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: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 75 |
| - num_epochs: 6 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
| | 0.3503 | 1.0 | 125 | 0.4379 | 0.83 | 0.8294 | |
| | 0.2971 | 2.0 | 250 | 0.4430 | 0.855 | 0.8549 | |
| | 0.2569 | 3.0 | 375 | 0.5001 | 0.87 | 0.87 | |
| | 0.1983 | 4.0 | 500 | 0.5181 | 0.855 | 0.8547 | |
| | 0.1342 | 5.0 | 625 | 0.5464 | 0.86 | 0.8598 | |
| | 0.1238 | 6.0 | 750 | 0.5883 | 0.87 | 0.8699 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 5.18.0 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.5 |
| - Tokenizers 0.23.2 |
|
|
