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---
license: mit
base_model: khadija69/xlmrBERTa_ASE_BIES
tags:
- generated_from_keras_callback
model-index:
- name: khadija69/xlmr_prep_modified_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/xlmr_prep_modified_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: 0.3659
- Train Accuracy: 0.6460
- Validation Loss: 0.9021
- Validation Accuracy: 0.5014
- 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': 1300, '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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.1906 | 0.4550 | 0.8755 | 0.4820 | 0 |
| 0.8317 | 0.5149 | 0.8012 | 0.4971 | 1 |
| 0.7156 | 0.5556 | 0.7896 | 0.5004 | 2 |
| 0.5780 | 0.5910 | 0.8720 | 0.4903 | 3 |
| 0.4616 | 0.6134 | 0.8959 | 0.4959 | 4 |
| 0.3659 | 0.6460 | 0.9021 | 0.5014 | 5 |
### Framework versions
- Transformers 4.41.2
- TensorFlow 2.15.0
- Datasets 2.19.2
- Tokenizers 0.19.1