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

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: 0.3182
- Validation Loss: 0.8903
- Train Accuracy: 0.75
- 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': 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 2.2603     | 2.0505          | 0.45           | 0     |
| 1.7907     | 1.6987          | 0.475          | 1     |
| 1.3820     | 1.4044          | 0.6            | 2     |
| 1.0496     | 1.2057          | 0.6            | 3     |
| 0.8393     | 1.0784          | 0.725          | 4     |
| 0.6652     | 0.9779          | 0.725          | 5     |
| 0.5508     | 0.9018          | 0.725          | 6     |
| 0.4662     | 0.8226          | 0.75           | 7     |
| 0.3664     | 0.8913          | 0.725          | 8     |
| 0.3182     | 0.8903          | 0.75           | 9     |


### Framework versions

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