arabert-emotions-classification
This model is a fine-tuned version of aubmindlab/bert-large-arabertv02 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2817
- F1: 0.7006
- Roc Auc: 0.7931
- Accuracy: 0.2769
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: 20
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 190 | 0.3665 | 0.5604 | 0.7049 | 0.1761 |
| No log | 2.0 | 380 | 0.3086 | 0.6755 | 0.7775 | 0.2564 |
| 0.3831 | 3.0 | 570 | 0.2953 | 0.6848 | 0.7812 | 0.2496 |
| 0.3831 | 4.0 | 760 | 0.2849 | 0.6933 | 0.7866 | 0.2615 |
| 0.3831 | 5.0 | 950 | 0.2817 | 0.7006 | 0.7931 | 0.2769 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
aubmindlab/bert-large-arabertv02