---
license: mit
base_model: khadija69/xlmrBERTa_ASE_BIES
tags:
- generated_from_keras_callback
model-index:
- name: khadija69/xlmrBERTa_ASE_BIES_2L
  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. -->

# khadija69/xlmrBERTa_ASE_BIES_2L

This model is a fine-tuned version of [khadija69/xlmrBERTa_ASE_BIES](https://huggingface.co/khadija69/xlmrBERTa_ASE_BIES) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3131
- Train Accuracy: 0.6628
- Validation Loss: 0.8504
- Validation Accuracy: 0.5429
- Epoch: 5

## 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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1900, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 500, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.7691     | 0.5281         | 0.7313          | 0.5404              | 0     |
| 0.7002     | 0.5495         | 0.6924          | 0.5462              | 1     |
| 0.5847     | 0.5784         | 0.7198          | 0.5422              | 2     |
| 0.4717     | 0.6141         | 0.7471          | 0.5408              | 3     |
| 0.3850     | 0.6386         | 0.8101          | 0.5441              | 4     |
| 0.3131     | 0.6628         | 0.8504          | 0.5429              | 5     |


### Framework versions

- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1