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: 1.2526
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1071 | 1.0 | 291 | 1.6964 |
| 1.6421 | 2.0 | 582 | 1.4279 |
| 1.4853 | 3.0 | 873 | 1.3924 |
| 1.4014 | 4.0 | 1164 | 1.3701 |
| 1.3388 | 5.0 | 1455 | 1.1944 |
| 1.283 | 6.0 | 1746 | 1.2795 |
| 1.2394 | 7.0 | 2037 | 1.2671 |
| 1.2014 | 8.0 | 2328 | 1.2084 |
| 1.1668 | 9.0 | 2619 | 1.1783 |
| 1.14 | 10.0 | 2910 | 1.2076 |
| 1.1277 | 11.0 | 3201 | 1.2081 |
| 1.1053 | 12.0 | 3492 | 1.1628 |
| 1.0819 | 13.0 | 3783 | 1.2544 |
| 1.0763 | 14.0 | 4074 | 1.1695 |
| 1.0634 | 15.0 | 4365 | 1.1157 |
| 1.0637 | 16.0 | 4656 | 1.2526 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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