---
license: mit
base_model: roberta-base
tags:
- generated_from_keras_callback
model-index:
- name: Thamer/roberta-fine-tuned
  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. -->

# Thamer/roberta-fine-tuned

This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3386
- Train Binary Accuracy: 0.8828
- Validation Loss: 0.5065
- Validation Binary Accuracy: 0.8114
- Train Accuracy: 0.4392
- Epoch: 4

## 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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 8416, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Binary Accuracy | Validation Loss | Validation Binary Accuracy | Train Accuracy | Epoch |
|:----------:|:---------------------:|:---------------:|:--------------------------:|:--------------:|:-----:|
| 0.3433     | 0.8777                | 0.5065          | 0.8114                     | 0.4392         | 0     |
| 0.3349     | 0.8815                | 0.5065          | 0.8114                     | 0.4392         | 1     |
| 0.3376     | 0.8812                | 0.5065          | 0.8114                     | 0.4392         | 2     |
| 0.3332     | 0.8816                | 0.5065          | 0.8114                     | 0.4392         | 3     |
| 0.3386     | 0.8828                | 0.5065          | 0.8114                     | 0.4392         | 4     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.3
- Tokenizers 0.13.3