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: 1.2464
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 |
---|---|---|---|
2.0986 | 1.0 | 291 | 1.6928 |
1.6392 | 2.0 | 582 | 1.4295 |
1.4873 | 3.0 | 873 | 1.3904 |
1.3995 | 4.0 | 1164 | 1.3811 |
1.341 | 5.0 | 1455 | 1.1973 |
1.2807 | 6.0 | 1746 | 1.2738 |
1.2394 | 7.0 | 2037 | 1.2633 |
1.1993 | 8.0 | 2328 | 1.2103 |
1.1656 | 9.0 | 2619 | 1.1839 |
1.1403 | 10.0 | 2910 | 1.2228 |
1.1289 | 11.0 | 3201 | 1.2081 |
1.104 | 12.0 | 3492 | 1.1652 |
1.0823 | 13.0 | 3783 | 1.2508 |
1.0736 | 14.0 | 4074 | 1.1687 |
1.0625 | 15.0 | 4365 | 1.1168 |
1.0626 | 16.0 | 4656 | 1.2464 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.13.3
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