---
license: mit
tags:
- generated_from_keras_callback
base_model: microsoft/deberta-v3-small
model-index:
- name: ai-detector-deberta
  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. -->

# ai-detector-deberta

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0031
- Train Accuracy: 0.9994
- Validation Loss: 0.0242
- Validation Accuracy: 0.9924
- Train Lr: 1e-07
- Epoch: 2

## 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': 'RMSprop', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': 100, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 1e-07, 'rho': 0.9, 'momentum': 0.0, 'epsilon': 1e-07, 'centered': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Train Lr | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:--------:|:-----:|
| 0.0707     | 0.9694         | 0.0260          | 0.9903              | 1e-05    | 0     |
| 0.0032     | 0.9993         | 0.0383          | 0.9882              | 1e-06    | 1     |
| 0.0031     | 0.9994         | 0.0242          | 0.9924              | 1e-07    | 2     |


### Framework versions

- Transformers 4.41.1
- TensorFlow 2.15.0
- Tokenizers 0.19.1