checkpoint
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6893
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9805 | 0.4 | 14970 | 0.9337 |
| 0.7891 | 0.8 | 29940 | 0.7608 |
| 0.5697 | 1.2 | 44910 | 0.7100 |
| 0.5658 | 1.6 | 59880 | 0.6664 |
| 0.5251 | 2.0 | 74850 | 0.6201 |
| 0.3758 | 2.4 | 89820 | 0.6756 |
| 0.3749 | 2.8 | 104790 | 0.6580 |
| 0.2743 | 3.2 | 119760 | 0.6885 |
| 0.2617 | 3.6 | 134730 | 0.7000 |
| 0.2253 | 4.0 | 149700 | 0.6893 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Base model
google-bert/bert-base-uncased