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: 1.2263
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1003 | 1.0 | 291 | 1.7025 |
| 1.6316 | 2.0 | 582 | 1.5260 |
| 1.4974 | 3.0 | 873 | 1.3546 |
| 1.397 | 4.0 | 1164 | 1.3399 |
| 1.3339 | 5.0 | 1455 | 1.2295 |
| 1.2868 | 6.0 | 1746 | 1.3672 |
| 1.2348 | 7.0 | 2037 | 1.3044 |
| 1.2022 | 8.0 | 2328 | 1.3370 |
| 1.1717 | 9.0 | 2619 | 1.2253 |
| 1.1395 | 10.0 | 2910 | 1.1759 |
| 1.1281 | 11.0 | 3201 | 1.1359 |
| 1.1124 | 12.0 | 3492 | 1.1801 |
| 1.0882 | 13.0 | 3783 | 1.2288 |
| 1.0764 | 14.0 | 4074 | 1.2054 |
| 1.0717 | 15.0 | 4365 | 1.2134 |
| 1.0625 | 16.0 | 4656 | 1.2263 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.0.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for sergi24sanchez/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased