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roberta-base-finetuned-paperconc3
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1262
- Precision: 0.7736
- Recall: 0.7442
- F1: 0.7586
- Accuracy: 0.9673
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 81 | 0.2172 | 0.6049 | 0.5180 | 0.5581 | 0.9433 |
| No log | 2.0 | 162 | 0.1489 | 0.7606 | 0.6448 | 0.6979 | 0.9582 |
| No log | 3.0 | 243 | 0.1262 | 0.7736 | 0.7442 | 0.7586 | 0.9673 |
| No log | 4.0 | 324 | 0.1288 | 0.7614 | 0.7759 | 0.7686 | 0.9666 |
| No log | 5.0 | 405 | 0.1340 | 0.7226 | 0.8372 | 0.7757 | 0.9633 |
| No log | 6.0 | 486 | 0.1356 | 0.7151 | 0.8436 | 0.7740 | 0.9625 |
| 0.1495 | 7.0 | 567 | 0.1365 | 0.7414 | 0.8245 | 0.7808 | 0.9688 |
| 0.1495 | 8.0 | 648 | 0.1555 | 0.7261 | 0.8351 | 0.7768 | 0.9635 |
| 0.1495 | 9.0 | 729 | 0.1597 | 0.7548 | 0.8393 | 0.7948 | 0.9669 |
| 0.1495 | 10.0 | 810 | 0.1605 | 0.7467 | 0.8351 | 0.7884 | 0.9666 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
