---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ratish/DBERT_CleanDesc_Collision_v2.1.4
  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_Collision_v2.1.4

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: 0.3438
- Validation Loss: 1.4467
- Train Accuracy: 0.5897
- Epoch: 11

## 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': 4575, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.6148     | 1.7151          | 0.3077         | 0     |
| 1.4783     | 1.7263          | 0.3077         | 1     |
| 1.3926     | 1.6779          | 0.4103         | 2     |
| 1.2462     | 1.5778          | 0.4359         | 3     |
| 1.0592     | 1.5154          | 0.4359         | 4     |
| 0.8814     | 1.5370          | 0.4615         | 5     |
| 0.7554     | 1.4250          | 0.5385         | 6     |
| 0.6303     | 1.4385          | 0.5641         | 7     |
| 0.5458     | 1.3870          | 0.4872         | 8     |
| 0.4808     | 1.3459          | 0.5385         | 9     |
| 0.4098     | 1.5049          | 0.5385         | 10    |
| 0.3438     | 1.4467          | 0.5897         | 11    |


### Framework versions

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