checkpoint
This model is a fine-tuned version of google-bert/bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5713
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: 16
- 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 |
|---|---|---|---|
| 0.9089 | 0.4 | 7373 | 0.8463 |
| 0.6975 | 0.8 | 14746 | 0.6603 |
| 0.5207 | 1.2 | 22119 | 0.6005 |
| 0.4985 | 1.6 | 29492 | 0.5558 |
| 0.4572 | 2.0 | 36865 | 0.5206 |
| 0.3228 | 2.4 | 44238 | 0.5485 |
| 0.305 | 2.8 | 51611 | 0.5243 |
| 0.2171 | 3.2 | 58984 | 0.5674 |
| 0.2057 | 3.6 | 66357 | 0.5713 |
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-large-uncased