AraBERT_token_classification_merged_10epochs
This model is a fine-tuned version of aubmindlab/bert-base-arabert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7055
- Precision: 0.0712
- Recall: 0.0412
- F1: 0.0522
- Accuracy: 0.6116
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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 254 | 1.4675 | 0.0 | 0.0 | 0.0 | 0.6786 |
1.218 | 2.0 | 508 | 1.4525 | 0.0 | 0.0 | 0.0 | 0.6777 |
1.218 | 3.0 | 762 | 1.5129 | 0.0024 | 0.0010 | 0.0014 | 0.6232 |
0.9307 | 4.0 | 1016 | 1.5492 | 0.0108 | 0.0020 | 0.0034 | 0.6614 |
0.9307 | 5.0 | 1270 | 1.5170 | 0.0055 | 0.0020 | 0.0030 | 0.6290 |
0.7449 | 6.0 | 1524 | 1.5224 | 0.0622 | 0.0376 | 0.0469 | 0.6104 |
0.7449 | 7.0 | 1778 | 1.6248 | 0.0450 | 0.0203 | 0.0280 | 0.6244 |
0.6337 | 8.0 | 2032 | 1.6913 | 0.0376 | 0.0142 | 0.0207 | 0.6276 |
0.6337 | 9.0 | 2286 | 1.6758 | 0.0666 | 0.0376 | 0.0481 | 0.6120 |
0.5539 | 10.0 | 2540 | 1.7055 | 0.0712 | 0.0412 | 0.0522 | 0.6116 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.12.1
- Datasets 2.13.2
- Tokenizers 0.13.3
- Downloads last month
- 5
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.