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roberta-base-roberta-base-TF-weight1-epoch15
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.8322
- Cls loss: 0.6900
- Lm loss: 4.1423
- Cls Accuracy: 0.5401
- Cls F1: 0.3788
- Cls Precision: 0.2917
- Cls Recall: 0.5401
- Perplexity: 62.95
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
|---|---|---|---|---|---|---|---|---|---|---|
| 5.3158 | 1.0 | 3470 | 4.9858 | 0.6910 | 4.2949 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 73.32 |
| 4.9772 | 2.0 | 6940 | 4.8876 | 0.6956 | 4.1920 | 0.4599 | 0.2898 | 0.2115 | 0.4599 | 66.15 |
| 4.8404 | 3.0 | 10410 | 4.8454 | 0.6901 | 4.1553 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 63.77 |
| 4.7439 | 4.0 | 13880 | 4.8177 | 0.6904 | 4.1274 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.02 |
| 4.6667 | 5.0 | 17350 | 4.8065 | 0.6903 | 4.1163 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.33 |
| 4.6018 | 6.0 | 20820 | 4.8081 | 0.6963 | 4.1119 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.06 |
| 4.5447 | 7.0 | 24290 | 4.8089 | 0.6912 | 4.1177 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.42 |
| 4.4944 | 8.0 | 27760 | 4.8128 | 0.6900 | 4.1228 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.73 |
| 4.4505 | 9.0 | 31230 | 4.8152 | 0.6905 | 4.1248 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.85 |
| 4.4116 | 10.0 | 34700 | 4.8129 | 0.6908 | 4.1221 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.69 |
| 4.3787 | 11.0 | 38170 | 4.8146 | 0.6906 | 4.1241 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 61.81 |
| 4.3494 | 12.0 | 41640 | 4.8229 | 0.6900 | 4.1329 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.36 |
| 4.3253 | 13.0 | 45110 | 4.8287 | 0.6900 | 4.1388 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.73 |
| 4.3075 | 14.0 | 48580 | 4.8247 | 0.6900 | 4.1347 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.47 |
| 4.2936 | 15.0 | 52050 | 4.8322 | 0.6900 | 4.1423 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 62.95 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
