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bert-base-uncased-finetuned-paper
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2326
- Precision: 0.7612
- Recall: 0.7456
- F1: 0.7533
- Accuracy: 0.9684
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 73 | 0.1917 | 0.6756 | 0.5175 | 0.5861 | 0.9484 |
| No log | 2.0 | 146 | 0.1402 | 0.7516 | 0.6988 | 0.7242 | 0.9678 |
| No log | 3.0 | 219 | 0.1747 | 0.7397 | 0.6813 | 0.7093 | 0.9659 |
| No log | 4.0 | 292 | 0.1627 | 0.6797 | 0.7632 | 0.7190 | 0.9633 |
| No log | 5.0 | 365 | 0.1720 | 0.7005 | 0.7456 | 0.7224 | 0.9661 |
| No log | 6.0 | 438 | 0.2029 | 0.7515 | 0.7339 | 0.7426 | 0.9688 |
| 0.0876 | 7.0 | 511 | 0.1928 | 0.7415 | 0.7632 | 0.7522 | 0.9700 |
| 0.0876 | 8.0 | 584 | 0.2016 | 0.7579 | 0.7690 | 0.7634 | 0.9708 |
| 0.0876 | 9.0 | 657 | 0.2051 | 0.7371 | 0.7544 | 0.7457 | 0.9684 |
| 0.0876 | 10.0 | 730 | 0.2153 | 0.7477 | 0.7281 | 0.7378 | 0.9693 |
| 0.0876 | 11.0 | 803 | 0.2284 | 0.7626 | 0.7515 | 0.7570 | 0.9693 |
| 0.0876 | 12.0 | 876 | 0.2223 | 0.7139 | 0.7515 | 0.7322 | 0.9682 |
| 0.0876 | 13.0 | 949 | 0.2274 | 0.7471 | 0.7515 | 0.7493 | 0.9690 |
| 0.0022 | 14.0 | 1022 | 0.2321 | 0.7695 | 0.7515 | 0.7604 | 0.9695 |
| 0.0022 | 15.0 | 1095 | 0.2367 | 0.7590 | 0.7368 | 0.7478 | 0.9690 |
| 0.0022 | 16.0 | 1168 | 0.2327 | 0.7612 | 0.7456 | 0.7533 | 0.9695 |
| 0.0022 | 17.0 | 1241 | 0.2367 | 0.7704 | 0.7456 | 0.7578 | 0.9690 |
| 0.0022 | 18.0 | 1314 | 0.2309 | 0.7529 | 0.7485 | 0.7507 | 0.9691 |
| 0.0022 | 19.0 | 1387 | 0.2358 | 0.7711 | 0.7485 | 0.7596 | 0.9686 |
| 0.0022 | 20.0 | 1460 | 0.2326 | 0.7612 | 0.7456 | 0.7533 | 0.9684 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
