---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_keras_callback
model-index:
- name: khadija69/debertav3_ASE_kgl_BIES2
  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/debertav3_ASE_kgl_BIES2

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6418
- Train Accuracy: 0.6024
- Validation Loss: 0.7774
- Validation Accuracy: 0.5724
- Epoch: 6

## 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': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 4000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, '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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.1865     | 0.4781         | 0.9186          | 0.5364              | 0     |
| 0.8841     | 0.5450         | 0.8210          | 0.5555              | 1     |
| 0.7972     | 0.5688         | 0.7997          | 0.5624              | 2     |
| 0.7395     | 0.5818         | 0.7777          | 0.5682              | 3     |
| 0.7011     | 0.5931         | 0.7836          | 0.5708              | 4     |
| 0.6760     | 0.5998         | 0.7845          | 0.5696              | 5     |
| 0.6418     | 0.6024         | 0.7774          | 0.5724              | 6     |


### Framework versions

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