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RoBERTa-perigon-news
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9548
Model description
The model was pre-trained for a MLM taskusing over 200K financial news articles obtaind from Perigon https://www.goperigon.com/.
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: 8.7e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.19
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4872 | 1.0 | 5480 | 1.3355 |
| 1.3571 | 2.0 | 10960 | 1.2488 |
| 1.3078 | 3.0 | 16440 | 1.2144 |
| 1.2425 | 4.0 | 21920 | 1.1634 |
| 1.2035 | 5.0 | 27400 | 1.1309 |
| 1.157 | 6.0 | 32880 | 1.0941 |
| 1.1268 | 7.0 | 38360 | 1.0696 |
| 1.098 | 8.0 | 43840 | 1.0466 |
| 1.0681 | 9.0 | 49320 | 1.0297 |
| 1.0356 | 10.0 | 54800 | 1.0168 |
| 1.0194 | 11.0 | 60280 | 1.0011 |
| 0.9941 | 12.0 | 65760 | 0.9843 |
| 0.981 | 13.0 | 71240 | 0.9716 |
| 0.9634 | 14.0 | 76720 | 0.9600 |
| 0.9511 | 15.0 | 82200 | 0.9546 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
