REBEL-ComSci
This model is a fine-tuned version of Babelscape/rebel-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.0770
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: 0.002
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|
| No log | 1.0 | 210 | 5.2197 |
| No log | 2.0 | 420 | 5.0887 |
| 5.8771 | 3.0 | 630 | 5.1124 |
| 5.8771 | 4.0 | 840 | 5.0977 |
| 4.5631 | 5.0 | 1050 | 5.0572 |
| 4.5631 | 6.0 | 1260 | 5.0645 |
| 4.5631 | 7.0 | 1470 | 5.0819 |
| 4.5209 | 8.0 | 1680 | 5.0690 |
| 4.5209 | 9.0 | 1890 | 5.0819 |
| 4.4896 | 10.0 | 2100 | 5.0770 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Tokenizers 0.13.1
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