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: 1.2247
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 |
|---|---|---|---|
| 2.0974 | 1.0 | 291 | 1.7007 |
| 1.631 | 2.0 | 582 | 1.5032 |
| 1.4987 | 3.0 | 873 | 1.3600 |
| 1.3987 | 4.0 | 1164 | 1.3352 |
| 1.3325 | 5.0 | 1455 | 1.2284 |
| 1.2854 | 6.0 | 1746 | 1.3716 |
| 1.232 | 7.0 | 2037 | 1.2937 |
| 1.2023 | 8.0 | 2328 | 1.3342 |
| 1.1664 | 9.0 | 2619 | 1.2240 |
| 1.1425 | 10.0 | 2910 | 1.1709 |
| 1.1266 | 11.0 | 3201 | 1.1263 |
| 1.1108 | 12.0 | 3492 | 1.1922 |
| 1.0878 | 13.0 | 3783 | 1.2260 |
| 1.0768 | 14.0 | 4074 | 1.2048 |
| 1.0751 | 15.0 | 4365 | 1.2156 |
| 1.061 | 16.0 | 4656 | 1.2247 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0
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Model tree for Nike25/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased