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: 1.2330
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 |
---|---|---|---|
2.1035 | 1.0 | 291 | 1.7061 |
1.6317 | 2.0 | 582 | 1.5071 |
1.4971 | 3.0 | 873 | 1.3600 |
1.3955 | 4.0 | 1164 | 1.3393 |
1.3299 | 5.0 | 1455 | 1.2405 |
1.2871 | 6.0 | 1746 | 1.3681 |
1.2325 | 7.0 | 2037 | 1.2985 |
1.2023 | 8.0 | 2328 | 1.3442 |
1.1691 | 9.0 | 2619 | 1.2195 |
1.1434 | 10.0 | 2910 | 1.1827 |
1.1251 | 11.0 | 3201 | 1.1261 |
1.1113 | 12.0 | 3492 | 1.1707 |
1.0868 | 13.0 | 3783 | 1.2133 |
1.0749 | 14.0 | 4074 | 1.2199 |
1.0725 | 15.0 | 4365 | 1.2171 |
1.0609 | 16.0 | 4656 | 1.2330 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for imp123/bert-base-uncased-issues-128
Base model
google-bert/bert-base-uncased