---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ratish/DBERT_CleanDesc_MAKE_v10.1
  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_CleanDesc_MAKE_v10.1

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: 0.1668
- Validation Loss: 0.7903
- Train Accuracy: 0.8
- Epoch: 14

## 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': 3090, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.2016     | 1.9470          | 0.425          | 0     |
| 1.6623     | 1.5632          | 0.575          | 1     |
| 1.2367     | 1.2743          | 0.575          | 2     |
| 0.9547     | 1.1049          | 0.75           | 3     |
| 0.7787     | 1.0268          | 0.725          | 4     |
| 0.6138     | 0.8950          | 0.75           | 5     |
| 0.5122     | 0.9161          | 0.75           | 6     |
| 0.4713     | 0.8417          | 0.8            | 7     |
| 0.4282     | 0.7698          | 0.75           | 8     |
| 0.3625     | 0.7982          | 0.75           | 9     |
| 0.2912     | 0.8342          | 0.775          | 10    |
| 0.2440     | 0.7864          | 0.775          | 11    |
| 0.2136     | 0.7688          | 0.775          | 12    |
| 0.1914     | 0.7626          | 0.8            | 13    |
| 0.1668     | 0.7903          | 0.8            | 14    |


### Framework versions

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