---
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_keras_callback
model-index:
- name: khadija69/mdebertaV3_BIES_stem_1K
  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/mdebertaV3_BIES_stem_1K

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: 0.8127
- Train Accuracy: 0.4340
- Validation Loss: 1.0993
- Validation Accuracy: 0.3815
- 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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.8993     | 0.2018         | 1.5357          | 0.2960              | 0     |
| 1.4273     | 0.3085         | 1.2327          | 0.3523              | 1     |
| 1.1660     | 0.3608         | 1.1347          | 0.3706              | 2     |
| 0.9903     | 0.3952         | 1.1114          | 0.3790              | 3     |
| 0.8813     | 0.4204         | 1.1030          | 0.3787              | 4     |
| 0.8127     | 0.4340         | 1.0993          | 0.3815              | 5     |


### Framework versions

- Transformers 4.42.3
- TensorFlow 2.15.0
- Datasets 2.20.0
- Tokenizers 0.19.1