bert-base-finetuned-ynat
This model is a fine-tuned version of klue/bert-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3653
- F1: 0.8701
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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 179 | 0.4209 | 0.8587 |
| No log | 2.0 | 358 | 0.3721 | 0.8677 |
| 0.3779 | 3.0 | 537 | 0.3607 | 0.8686 |
| 0.3779 | 4.0 | 716 | 0.3659 | 0.8688 |
| 0.3779 | 5.0 | 895 | 0.3653 | 0.8701 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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