---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ateffal/question-recognizer
  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. -->

# ateffal/question-recognizer

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0006
- Validation Loss: 0.0119
- Train Accuracy: 0.998
- Epoch: 9

## 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': 5100, '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 | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.0953     | 0.0062          | 0.9985         | 0     |
| 0.0196     | 0.0105          | 0.9972         | 1     |
| 0.0076     | 0.0051          | 0.9988         | 2     |
| 0.0081     | 0.0048          | 0.9985         | 3     |
| 0.0052     | 0.0117          | 0.998          | 4     |
| 0.0030     | 0.0101          | 0.9982         | 5     |
| 0.0019     | 0.0112          | 0.998          | 6     |
| 0.0013     | 0.0113          | 0.9982         | 7     |
| 0.0008     | 0.0120          | 0.998          | 8     |
| 0.0006     | 0.0119          | 0.998          | 9     |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.1.0
- Tokenizers 0.13.2