metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: IE_model
results: []
IE_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: 0.4341
- Accuracy: 0.9007
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 |
|---|---|---|---|---|
| 0.9432 | 1.0 | 574 | 0.5054 | 0.8537 |
| 0.4765 | 2.0 | 1148 | 0.4133 | 0.8589 |
| 0.4471 | 3.0 | 1722 | 0.4228 | 0.8693 |
| 0.3666 | 4.0 | 2296 | 0.4627 | 0.8815 |
| 0.3508 | 5.0 | 2870 | 0.3704 | 0.8833 |
| 0.325 | 6.0 | 3444 | 0.3704 | 0.9024 |
| 0.2662 | 7.0 | 4018 | 0.3733 | 0.9024 |
| 0.226 | 8.0 | 4592 | 0.4024 | 0.8972 |
| 0.1978 | 9.0 | 5166 | 0.4198 | 0.9042 |
| 0.186 | 10.0 | 5740 | 0.4341 | 0.9007 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2