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: 1.2222
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 |
---|---|---|---|
2.0987 | 1.0 | 291 | 1.6985 |
1.6308 | 2.0 | 582 | 1.5183 |
1.4968 | 3.0 | 873 | 1.3575 |
1.3963 | 4.0 | 1164 | 1.3388 |
1.3329 | 5.0 | 1455 | 1.2376 |
1.2854 | 6.0 | 1746 | 1.3704 |
1.2359 | 7.0 | 2037 | 1.2990 |
1.2064 | 8.0 | 2328 | 1.3360 |
1.1628 | 9.0 | 2619 | 1.2264 |
1.1406 | 10.0 | 2910 | 1.1664 |
1.1286 | 11.0 | 3201 | 1.1303 |
1.1123 | 12.0 | 3492 | 1.1831 |
1.0896 | 13.0 | 3783 | 1.2102 |
1.0764 | 14.0 | 4074 | 1.2081 |
1.0716 | 15.0 | 4365 | 1.2217 |
1.06 | 16.0 | 4656 | 1.2222 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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