bart-mlm-pubmed-45
This model is a fine-tuned version of facebook/bart-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1797
- Rouge2 Precision: 0.4333
- Rouge2 Recall: 0.3331
- Rouge2 Fmeasure: 0.3684
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
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Rouge2 Precision |
Rouge2 Recall |
Rouge2 Fmeasure |
| 1.7989 |
1.0 |
663 |
1.3385 |
0.4097 |
0.3086 |
0.3444 |
| 1.5072 |
2.0 |
1326 |
1.2582 |
0.4218 |
0.3213 |
0.3569 |
| 1.4023 |
3.0 |
1989 |
1.2236 |
0.4207 |
0.3211 |
0.3562 |
| 1.2205 |
4.0 |
2652 |
1.2025 |
0.4359 |
0.3331 |
0.3696 |
| 1.1584 |
5.0 |
3315 |
1.1910 |
0.4304 |
0.3307 |
0.3658 |
| 1.1239 |
6.0 |
3978 |
1.1830 |
0.4247 |
0.3279 |
0.3618 |
| 1.0384 |
7.0 |
4641 |
1.1761 |
0.4308 |
0.3325 |
0.367 |
| 1.0168 |
8.0 |
5304 |
1.1762 |
0.4314 |
0.3336 |
0.368 |
| 0.9966 |
9.0 |
5967 |
1.1773 |
0.4335 |
0.3341 |
0.369 |
| 0.961 |
10.0 |
6630 |
1.1797 |
0.4333 |
0.3331 |
0.3684 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3
