metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: label_4_Test
results: []
label_4_Test
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: 0.0461
- Accuracy: 0.9899
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 | 99 | 0.0693 | 0.9798 |
| No log | 2.0 | 198 | 0.0522 | 0.9798 |
| No log | 3.0 | 297 | 0.0581 | 0.9697 |
| No log | 4.0 | 396 | 0.0394 | 0.9899 |
| No log | 5.0 | 495 | 0.0367 | 0.9899 |
| 0.1504 | 6.0 | 594 | 0.0506 | 0.9899 |
| 0.1504 | 7.0 | 693 | 0.0402 | 0.9899 |
| 0.1504 | 8.0 | 792 | 0.0476 | 0.9899 |
| 0.1504 | 9.0 | 891 | 0.0453 | 0.9899 |
| 0.1504 | 10.0 | 990 | 0.0461 | 0.9899 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2