bert-base-uncased-issues-128
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1389
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.9863 | 1.0 | 1163 | 1.5917 |
1.579 | 2.0 | 2326 | 1.4668 |
1.4305 | 3.0 | 3489 | 1.3947 |
1.3367 | 4.0 | 4652 | 1.2889 |
1.2748 | 5.0 | 5815 | 1.3377 |
1.2184 | 6.0 | 6978 | 1.3370 |
1.1708 | 7.0 | 8141 | 1.2595 |
1.1309 | 8.0 | 9304 | 1.3044 |
1.0896 | 9.0 | 10467 | 1.2314 |
1.0614 | 10.0 | 11630 | 1.1699 |
1.0296 | 11.0 | 12793 | 1.2066 |
0.9896 | 12.0 | 13956 | 1.2158 |
0.983 | 13.0 | 15119 | 1.1289 |
0.9619 | 14.0 | 16282 | 1.1427 |
0.9387 | 15.0 | 17445 | 1.0767 |
0.9205 | 16.0 | 18608 | 1.1389 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.2.1
- Tokenizers 0.12.1
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