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---
license: mit
base_model: khadija69/xlmRobertaLarge_BIES_stem_1K_4
tags:
- generated_from_keras_callback
model-index:
- name: khadija69/xlmRobertaLarge_BIES_stem_1K_5
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/xlmRobertaLarge_BIES_stem_1K_5
This model is a fine-tuned version of [khadija69/xlmRobertaLarge_BIES_stem_1K_4](https://huggingface.co/khadija69/xlmRobertaLarge_BIES_stem_1K_4) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2523
- Train Accuracy: 0.6422
- Validation Loss: 0.8771
- Validation Accuracy: 0.5658
- 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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.7968 | 0.5139 | 0.7148 | 0.5549 | 0 |
| 0.7021 | 0.5252 | 0.7208 | 0.5592 | 1 |
| 0.5547 | 0.5602 | 0.7998 | 0.5531 | 2 |
| 0.4235 | 0.6001 | 0.8239 | 0.5628 | 3 |
| 0.3137 | 0.6255 | 0.8664 | 0.5627 | 4 |
| 0.2523 | 0.6422 | 0.8771 | 0.5658 | 5 |
### Framework versions
- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1
|