metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa_token_classification_AraEval24_aug800
results: []
RoBERTa_token_classification_AraEval24_aug800
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5882
- Precision: 0.0607
- Recall: 0.0717
- F1: 0.0658
- Accuracy: 0.6965
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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.7043 | 1.0 | 1839 | 1.0921 | 0.0244 | 0.0115 | 0.0156 | 0.7401 |
| 0.4043 | 2.0 | 3678 | 1.1721 | 0.0428 | 0.0339 | 0.0378 | 0.7080 |
| 0.3146 | 3.0 | 5517 | 1.2162 | 0.0565 | 0.0583 | 0.0574 | 0.7032 |
| 0.2459 | 4.0 | 7356 | 1.3033 | 0.0641 | 0.0697 | 0.0668 | 0.7021 |
| 0.2155 | 5.0 | 9195 | 1.2839 | 0.0619 | 0.0523 | 0.0567 | 0.7322 |
| 0.1775 | 6.0 | 11034 | 1.3535 | 0.0653 | 0.0627 | 0.0640 | 0.7184 |
| 0.1598 | 7.0 | 12873 | 1.4153 | 0.0654 | 0.0702 | 0.0677 | 0.7092 |
| 0.1442 | 8.0 | 14712 | 1.5081 | 0.0636 | 0.0712 | 0.0672 | 0.6949 |
| 0.1287 | 9.0 | 16551 | 1.5040 | 0.0646 | 0.0687 | 0.0666 | 0.7068 |
| 0.108 | 10.0 | 18390 | 1.5882 | 0.0607 | 0.0717 | 0.0658 | 0.6965 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1
- Datasets 2.13.2
- Tokenizers 0.13.3