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: 1.2311
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 |
|---|---|---|---|
| 2.1008 | 1.0 | 291 | 1.7013 |
| 1.6347 | 2.0 | 582 | 1.5253 |
| 1.4976 | 3.0 | 873 | 1.3564 |
| 1.3963 | 4.0 | 1164 | 1.3459 |
| 1.3333 | 5.0 | 1455 | 1.2349 |
| 1.2849 | 6.0 | 1746 | 1.3587 |
| 1.2319 | 7.0 | 2037 | 1.3066 |
| 1.2078 | 8.0 | 2328 | 1.3463 |
| 1.167 | 9.0 | 2619 | 1.2071 |
| 1.1417 | 10.0 | 2910 | 1.1766 |
| 1.1259 | 11.0 | 3201 | 1.1292 |
| 1.1097 | 12.0 | 3492 | 1.1873 |
| 1.0884 | 13.0 | 3783 | 1.2220 |
| 1.0792 | 14.0 | 4074 | 1.2137 |
| 1.0741 | 15.0 | 4365 | 1.2251 |
| 1.0624 | 16.0 | 4656 | 1.2311 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for athlonxpgzw/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased