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: 1.2229
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 OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|
| 2.1 | 1.0 | 291 | 1.7043 |
| 1.6306 | 2.0 | 582 | 1.5224 |
| 1.4948 | 3.0 | 873 | 1.3533 |
| 1.3995 | 4.0 | 1164 | 1.3313 |
| 1.3352 | 5.0 | 1455 | 1.2348 |
| 1.2866 | 6.0 | 1746 | 1.3613 |
| 1.2314 | 7.0 | 2037 | 1.3021 |
| 1.2025 | 8.0 | 2328 | 1.3274 |
| 1.1666 | 9.0 | 2619 | 1.2164 |
| 1.1376 | 10.0 | 2910 | 1.1748 |
| 1.1283 | 11.0 | 3201 | 1.1241 |
| 1.1086 | 12.0 | 3492 | 1.1772 |
| 1.0872 | 13.0 | 3783 | 1.2140 |
| 1.0773 | 14.0 | 4074 | 1.2059 |
| 1.072 | 15.0 | 4365 | 1.2150 |
| 1.0629 | 16.0 | 4656 | 1.2229 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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Model tree for math-hiyoko/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased