---
tags:
- generated_from_keras_callback
model-index:
- name: AHarbury/debiasNLPFinal
  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. -->

# AHarbury/debiasNLPFinal

This model is a fine-tuned version of [d4data/bias-detection-model](https://huggingface.co/d4data/bias-detection-model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4182
- Train Accuracy: 0.7945
- Validation Loss: 0.6095
- Validation Accuracy: 0.6977
- 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': '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': 5e-05, 'decay_steps': 80700, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.6165     | 0.6467         | 0.5900          | 0.6637              | 0     |
| 0.5788     | 0.6844         | 0.5746          | 0.6892              | 1     |
| 0.5392     | 0.7147         | 0.5621          | 0.7017              | 2     |
| 0.5016     | 0.7416         | 0.5784          | 0.6967              | 3     |
| 0.4573     | 0.7714         | 0.5928          | 0.6957              | 4     |
| 0.4182     | 0.7945         | 0.6095          | 0.6977              | 5     |


### Framework versions

- Transformers 4.29.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3