metadata
base_model: aubmindlab/bert-large-arabertv02-twitter
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Araberv2_large
results: []
Araberv2_large
This model is a fine-tuned version of aubmindlab/bert-large-arabertv02-twitter on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3745
- F1: 0.5436
- F1 Macro: 0.1187
- Roc Auc: 0.7222
- Accuracy: 0.5531
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F1 Macro | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.3412 | 1.0 | 507 | 0.3815 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3775 | 2.0 | 1014 | 0.3745 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3768 | 3.0 | 1521 | 0.3914 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3764 | 4.0 | 2028 | 0.3745 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3714 | 5.0 | 2535 | 0.3870 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3697 | 6.0 | 3042 | 0.3835 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3688 | 7.0 | 3549 | 0.4026 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
| 0.3654 | 8.0 | 4056 | 0.4771 | 0.5436 | 0.1187 | 0.7222 | 0.5531 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3