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bert-large-cased-finetuned-lowR100-3-cased-DA-20
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5250
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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 1 | 6.8611 |
6.5268 | 2.0 | 2 | 8.5069 |
6.5268 | 3.0 | 3 | 6.4383 |
6.3552 | 4.0 | 4 | 5.2540 |
6.3552 | 5.0 | 5 | 6.2490 |
5.5713 | 6.0 | 6 | 5.8587 |
5.5713 | 7.0 | 7 | 5.6369 |
5.0248 | 8.0 | 8 | 5.1667 |
5.0248 | 9.0 | 9 | 4.8407 |
4.364 | 10.0 | 10 | 5.0590 |
4.364 | 11.0 | 11 | 4.8647 |
3.6607 | 12.0 | 12 | 3.3072 |
3.6607 | 13.0 | 13 | 3.4963 |
3.3901 | 14.0 | 14 | 4.0039 |
3.3901 | 15.0 | 15 | 3.5993 |
3.1245 | 16.0 | 16 | 2.2179 |
3.1245 | 17.0 | 17 | 1.6414 |
3.1906 | 18.0 | 18 | 3.1965 |
3.1906 | 19.0 | 19 | 3.1463 |
2.7243 | 20.0 | 20 | 3.1866 |
2.7243 | 21.0 | 21 | 1.0648 |
2.944 | 22.0 | 22 | 3.2413 |
2.944 | 23.0 | 23 | 3.1838 |
2.7114 | 24.0 | 24 | 3.8036 |
2.7114 | 25.0 | 25 | 2.2897 |
2.4176 | 26.0 | 26 | 3.6953 |
2.4176 | 27.0 | 27 | 3.3176 |
2.4277 | 28.0 | 28 | 2.9940 |
2.4277 | 29.0 | 29 | 3.0186 |
2.4099 | 30.0 | 30 | 3.0385 |
2.4099 | 31.0 | 31 | 1.9323 |
2.2141 | 32.0 | 32 | 2.2952 |
2.2141 | 33.0 | 33 | 3.5302 |
2.4007 | 34.0 | 34 | 3.7787 |
2.4007 | 35.0 | 35 | 3.3718 |
2.2619 | 36.0 | 36 | 2.2895 |
2.2619 | 37.0 | 37 | 2.7433 |
2.4834 | 38.0 | 38 | 3.5129 |
2.4834 | 39.0 | 39 | 1.7792 |
2.122 | 40.0 | 40 | 2.5250 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2