metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: TC_model
results: []
TC_model
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: 0.5923
- Accuracy: 0.9405
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 85 | 0.6354 | 0.9167 |
| No log | 2.0 | 170 | 0.5542 | 0.9048 |
| No log | 3.0 | 255 | 0.4928 | 0.9405 |
| No log | 4.0 | 340 | 0.5524 | 0.9405 |
| No log | 5.0 | 425 | 0.5733 | 0.9405 |
| 0.0575 | 6.0 | 510 | 0.5815 | 0.9405 |
| 0.0575 | 7.0 | 595 | 0.5857 | 0.9405 |
| 0.0575 | 8.0 | 680 | 0.5896 | 0.9405 |
| 0.0575 | 9.0 | 765 | 0.5922 | 0.9405 |
| 0.0575 | 10.0 | 850 | 0.5923 | 0.9405 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2