kobigbird-bert-base-finetuned-klue
This model is a fine-tuned version of monologg/kobigbird-bert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8347
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
5.3957 | 0.13 | 500 | 3.7603 |
3.2242 | 0.26 | 1000 | 2.3961 |
2.0812 | 0.4 | 1500 | 1.5552 |
1.6198 | 0.53 | 2000 | 1.3609 |
1.447 | 0.66 | 2500 | 1.2270 |
1.3438 | 0.79 | 3000 | 1.1321 |
1.2399 | 0.93 | 3500 | 1.0973 |
1.1976 | 1.06 | 4000 | 1.0418 |
1.1177 | 1.19 | 4500 | 1.0301 |
1.0811 | 1.32 | 5000 | 1.0232 |
1.0506 | 1.45 | 5500 | 0.9971 |
1.0293 | 1.59 | 6000 | 0.9580 |
1.0196 | 1.72 | 6500 | 0.9551 |
0.9846 | 1.85 | 7000 | 0.9274 |
0.9702 | 1.98 | 7500 | 0.9286 |
0.9224 | 2.11 | 8000 | 0.8961 |
0.8867 | 2.25 | 8500 | 0.9193 |
0.8711 | 2.38 | 9000 | 0.8727 |
0.883 | 2.51 | 9500 | 0.8790 |
0.8513 | 2.64 | 10000 | 0.8830 |
0.8709 | 2.78 | 10500 | 0.8604 |
0.8766 | 2.91 | 11000 | 0.8260 |
0.7976 | 3.04 | 11500 | 0.8401 |
0.7724 | 3.17 | 12000 | 0.8617 |
0.78 | 3.3 | 12500 | 0.8601 |
0.7566 | 3.44 | 13000 | 0.8657 |
0.7407 | 3.57 | 13500 | 0.8347 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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