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bert-test
This model is a fine-tuned version of klue/roberta-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3693
- F1: 0.8718
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.2776 | 1.0 | 714 | 0.4056 | 0.8603 |
| 0.2862 | 2.0 | 1428 | 0.3693 | 0.8718 |
Framework versions
- Transformers 4.27.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
