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: 1.1725
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1083 | 1.0 | 291 | 1.6830 |
| 1.6339 | 2.0 | 582 | 1.3684 |
| 1.4793 | 3.0 | 873 | 1.4214 |
| 1.3969 | 4.0 | 1164 | 1.4244 |
| 1.3425 | 5.0 | 1455 | 1.2755 |
| 1.2837 | 6.0 | 1746 | 1.3189 |
| 1.2316 | 7.0 | 2037 | 1.2051 |
| 1.2106 | 8.0 | 2328 | 1.2933 |
| 1.1779 | 9.0 | 2619 | 1.2659 |
| 1.1491 | 10.0 | 2910 | 1.2092 |
| 1.1254 | 11.0 | 3201 | 1.2649 |
| 1.0971 | 12.0 | 3492 | 1.1623 |
| 1.0925 | 13.0 | 3783 | 1.1459 |
| 1.0772 | 14.0 | 4074 | 1.0685 |
| 1.0648 | 15.0 | 4365 | 1.2594 |
| 1.0651 | 16.0 | 4656 | 1.1725 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for haesun/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased