hana-16-0.00001
This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4975
- Accuracy: 0.7112
- F1: 0.7098
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: 1e-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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.1467 | 1.0 | 4388 | 1.8577 | 0.7118 | 0.7052 |
0.1394 | 2.0 | 8776 | 1.8887 | 0.7140 | 0.7101 |
0.123 | 3.0 | 13164 | 2.1311 | 0.7118 | 0.7097 |
0.072 | 4.0 | 17552 | 2.3925 | 0.7111 | 0.7094 |
0.0364 | 5.0 | 21940 | 2.4975 | 0.7112 | 0.7098 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
klue/roberta-large