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: 1.2331
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
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1023 | 1.0 | 291 | 1.7007 |
| 1.6345 | 2.0 | 582 | 1.5119 |
| 1.4924 | 3.0 | 873 | 1.3620 |
| 1.4024 | 4.0 | 1164 | 1.3346 |
| 1.3393 | 5.0 | 1455 | 1.2563 |
| 1.2689 | 6.0 | 1746 | 1.3461 |
| 1.2204 | 7.0 | 2037 | 1.2857 |
| 1.2078 | 8.0 | 2328 | 1.3402 |
| 1.178 | 9.0 | 2619 | 1.2064 |
| 1.1321 | 10.0 | 2910 | 1.1628 |
| 1.129 | 11.0 | 3201 | 1.1414 |
| 1.0984 | 12.0 | 3492 | 1.1755 |
| 1.0905 | 13.0 | 3783 | 1.2250 |
| 1.0756 | 14.0 | 4074 | 1.2226 |
| 1.0702 | 15.0 | 4365 | 1.2198 |
| 1.0495 | 16.0 | 4656 | 1.2331 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1
- Datasets 2.12.0
- Tokenizers 0.13.3
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