metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: claim-classifier
results: []
claim-classifier
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3432
- Accuracy: 0.8889
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.048 | 1.0 | 562 | 0.3966 | 0.8669 |
| 0.3896 | 2.0 | 1124 | 0.4440 | 0.8669 |
| 0.4783 | 3.0 | 1686 | 0.3893 | 0.8699 |
| 0.4792 | 4.0 | 2248 | 0.4019 | 0.8689 |
| 1.2405 | 5.0 | 2810 | 0.3883 | 0.8729 |
| 0.0996 | 6.0 | 3372 | 0.3673 | 0.8669 |
| 0.4833 | 7.0 | 3934 | 0.3873 | 0.8759 |
| 0.2461 | 8.0 | 4496 | 0.3646 | 0.8659 |
| 0.0977 | 9.0 | 5058 | 0.3432 | 0.8889 |
| 0.0682 | 10.0 | 5620 | 0.3458 | 0.8919 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.8.1
- Datasets 2.13.2
- Tokenizers 0.13.3