|
--- |
|
license: mit |
|
base_model: Davlan/xlm-roberta-base-finetuned-arabic |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: betteib/xlm-tn-20epochs-lr |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information Keras had access to. You should |
|
probably proofread and complete it, then remove this comment. --> |
|
|
|
# betteib/xlm-tn-20epochs-lr |
|
|
|
This model is a fine-tuned version of [Davlan/xlm-roberta-base-finetuned-arabic](https://huggingface.co/Davlan/xlm-roberta-base-finetuned-arabic) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Train Loss: 7.2561 |
|
- Train Accuracy: 0.0273 |
|
- Validation Loss: 7.0588 |
|
- Validation Accuracy: 0.0289 |
|
- Epoch: 4 |
|
|
|
## 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: |
|
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 4464, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 496, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.03} |
|
- training_precision: float32 |
|
|
|
### Training results |
|
|
|
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
|
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
|
| 9.6176 | 0.0035 | 9.2319 | 0.0048 | 0 | |
|
| 8.9356 | 0.0059 | 8.5303 | 0.0071 | 1 | |
|
| 8.1494 | 0.0100 | 7.7161 | 0.0137 | 2 | |
|
| 7.5554 | 0.0180 | 7.2709 | 0.0281 | 3 | |
|
| 7.2561 | 0.0273 | 7.0588 | 0.0289 | 4 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- TensorFlow 2.12.0 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.13.3 |
|
|
