bert-base-News-News
This model is a fine-tuned version of klue/bert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3536
- Accuracy: 0.9462
- F1: 0.9463
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.0299 | 1.0 | 614 | 0.3664 | 0.9350 | 0.9347 |
| 0.0149 | 2.0 | 1228 | 0.3766 | 0.9422 | 0.9423 |
| 0.0059 | 3.0 | 1842 | 0.3536 | 0.9462 | 0.9463 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.13.3
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