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bert-base-uncased-bert-base-uncased-mc-weight0-epoch15
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.3651
- Cls loss: 2.9223
- Lm loss: 4.3649
- Cls Accuracy: 0.0248
- Cls F1: 0.0057
- Cls Precision: 0.0061
- Cls Recall: 0.0248
- Perplexity: 78.64
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| 4.8711 | 1.0 | 3470 | 4.5156 | 2.9252 | 4.5155 | 0.0213 | 0.0047 | 0.0042 | 0.0213 | 91.42 |
| 4.483 | 2.0 | 6940 | 4.4193 | 2.9248 | 4.4191 | 0.0219 | 0.0048 | 0.0042 | 0.0219 | 83.02 |
| 4.3345 | 3.0 | 10410 | 4.3684 | 2.9244 | 4.3682 | 0.0219 | 0.0048 | 0.0042 | 0.0219 | 78.91 |
| 4.2266 | 4.0 | 13880 | 4.3445 | 2.9241 | 4.3443 | 0.0225 | 0.0049 | 0.0043 | 0.0225 | 77.04 |
| 4.1388 | 5.0 | 17350 | 4.3260 | 2.9237 | 4.3258 | 0.0231 | 0.0050 | 0.0044 | 0.0231 | 75.63 |
| 4.0644 | 6.0 | 20820 | 4.3299 | 2.9234 | 4.3297 | 0.0231 | 0.0050 | 0.0044 | 0.0231 | 75.92 |
| 3.999 | 7.0 | 24290 | 4.3278 | 2.9232 | 4.3276 | 0.0231 | 0.0059 | 0.0061 | 0.0231 | 75.76 |
| 3.9426 | 8.0 | 27760 | 4.3269 | 2.9230 | 4.3267 | 0.0231 | 0.0059 | 0.0061 | 0.0231 | 75.70 |
| 3.8929 | 9.0 | 31230 | 4.3324 | 2.9228 | 4.3322 | 0.0248 | 0.0061 | 0.0062 | 0.0248 | 76.11 |
| 3.8488 | 10.0 | 34700 | 4.3382 | 2.9227 | 4.3380 | 0.0248 | 0.0061 | 0.0064 | 0.0248 | 76.55 |
| 3.8116 | 11.0 | 38170 | 4.3461 | 2.9225 | 4.3459 | 0.0242 | 0.0057 | 0.0061 | 0.0242 | 77.16 |
| 3.7791 | 12.0 | 41640 | 4.3537 | 2.9224 | 4.3535 | 0.0248 | 0.0057 | 0.0061 | 0.0248 | 77.75 |
| 3.7532 | 13.0 | 45110 | 4.3593 | 2.9223 | 4.3591 | 0.0248 | 0.0057 | 0.0061 | 0.0248 | 78.19 |
| 3.7321 | 14.0 | 48580 | 4.3588 | 2.9223 | 4.3586 | 0.0248 | 0.0057 | 0.0061 | 0.0248 | 78.15 |
| 3.7182 | 15.0 | 52050 | 4.3651 | 2.9223 | 4.3649 | 0.0248 | 0.0057 | 0.0061 | 0.0248 | 78.64 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
