---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ratish/DBERT_Fault_LR_v2.1
  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. -->

# ratish/DBERT_Fault_LR_v2.1

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: 0.1501
- Validation Loss: 0.6305
- Train Accuracy: 0.7179
- Epoch: 29

## 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-06, 'decay_steps': 9120, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.6963     | 0.6916          | 0.5128         | 0     |
| 0.6774     | 0.6929          | 0.5128         | 1     |
| 0.6631     | 0.7000          | 0.5128         | 2     |
| 0.6580     | 0.7070          | 0.5128         | 3     |
| 0.6409     | 0.7104          | 0.5128         | 4     |
| 0.6296     | 0.7015          | 0.5128         | 5     |
| 0.6115     | 0.6866          | 0.5128         | 6     |
| 0.5940     | 0.6573          | 0.5897         | 7     |
| 0.5616     | 0.6263          | 0.5897         | 8     |
| 0.5230     | 0.5886          | 0.6667         | 9     |
| 0.4890     | 0.5608          | 0.7179         | 10    |
| 0.4523     | 0.5386          | 0.7436         | 11    |
| 0.4307     | 0.5424          | 0.7179         | 12    |
| 0.4013     | 0.5261          | 0.7179         | 13    |
| 0.3893     | 0.4976          | 0.7436         | 14    |
| 0.3634     | 0.5459          | 0.6923         | 15    |
| 0.3337     | 0.4893          | 0.7436         | 16    |
| 0.3243     | 0.5490          | 0.7179         | 17    |
| 0.3083     | 0.5091          | 0.7179         | 18    |
| 0.2815     | 0.5457          | 0.7179         | 19    |
| 0.2654     | 0.5692          | 0.7179         | 20    |
| 0.2535     | 0.4808          | 0.7436         | 21    |
| 0.2504     | 0.5912          | 0.6923         | 22    |
| 0.2132     | 0.6228          | 0.6923         | 23    |
| 0.1962     | 0.5834          | 0.7179         | 24    |
| 0.2136     | 0.5261          | 0.7692         | 25    |
| 0.1895     | 0.6210          | 0.7179         | 26    |
| 0.1722     | 0.7140          | 0.7179         | 27    |
| 0.1580     | 0.6532          | 0.6923         | 28    |
| 0.1501     | 0.6305          | 0.7179         | 29    |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3