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: 1.2246
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 |
|---|---|---|---|
| 2.1034 | 1.0 | 291 | 1.6900 |
| 1.633 | 2.0 | 582 | 1.5064 |
| 1.4987 | 3.0 | 873 | 1.3561 |
| 1.3959 | 4.0 | 1164 | 1.3319 |
| 1.3338 | 5.0 | 1455 | 1.2403 |
| 1.2846 | 6.0 | 1746 | 1.3655 |
| 1.2322 | 7.0 | 2037 | 1.3020 |
| 1.205 | 8.0 | 2328 | 1.3446 |
| 1.1691 | 9.0 | 2619 | 1.2094 |
| 1.1417 | 10.0 | 2910 | 1.1771 |
| 1.1246 | 11.0 | 3201 | 1.1232 |
| 1.1113 | 12.0 | 3492 | 1.1807 |
| 1.0918 | 13.0 | 3783 | 1.2276 |
| 1.0766 | 14.0 | 4074 | 1.2099 |
| 1.0701 | 15.0 | 4365 | 1.2340 |
| 1.0619 | 16.0 | 4656 | 1.2246 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.7.1+cu118
- Datasets 4.5.0
- Tokenizers 0.22.2
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Model tree for srmjfba/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased