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: 1.1922
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 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 |
|---|---|---|---|
| 2.1169 | 1.0 | 292 | 1.6771 |
| 1.6363 | 2.0 | 584 | 1.4808 |
| 1.4818 | 3.0 | 876 | 1.4376 |
| 1.3859 | 4.0 | 1168 | 1.3753 |
| 1.339 | 5.0 | 1460 | 1.2945 |
| 1.283 | 6.0 | 1752 | 1.2843 |
| 1.2383 | 7.0 | 2044 | 1.1759 |
| 1.2099 | 8.0 | 2336 | 1.3379 |
| 1.1649 | 9.0 | 2628 | 1.1895 |
| 1.1578 | 10.0 | 2920 | 1.1954 |
| 1.1257 | 11.0 | 3212 | 1.1181 |
| 1.1047 | 12.0 | 3504 | 1.2260 |
| 1.1003 | 13.0 | 3796 | 1.0715 |
| 1.0793 | 14.0 | 4088 | 1.1815 |
| 1.0732 | 15.0 | 4380 | 1.1907 |
| 1.0489 | 16.0 | 4672 | 1.1922 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for jewoos/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased