---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ratish/DBERT_ZS_CleanCollision_v1
  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_ZS_CleanCollision_v1

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: 0.0014
- Validation Loss: 0.0010
- Train Accuracy: 1.0
- Epoch: 27

## 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': 9960, '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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.7535     | 0.3396          | 1.0            | 0     |
| 0.2209     | 0.0995          | 1.0            | 1     |
| 0.0806     | 0.0471          | 1.0            | 2     |
| 0.0450     | 0.0296          | 1.0            | 3     |
| 0.0305     | 0.0210          | 1.0            | 4     |
| 0.0222     | 0.0157          | 1.0            | 5     |
| 0.0175     | 0.0122          | 1.0            | 6     |
| 0.0139     | 0.0098          | 1.0            | 7     |
| 0.0111     | 0.0080          | 1.0            | 8     |
| 0.0094     | 0.0066          | 1.0            | 9     |
| 0.0077     | 0.0056          | 1.0            | 10    |
| 0.0067     | 0.0048          | 1.0            | 11    |
| 0.0059     | 0.0042          | 1.0            | 12    |
| 0.0053     | 0.0037          | 1.0            | 13    |
| 0.0044     | 0.0032          | 1.0            | 14    |
| 0.0041     | 0.0029          | 1.0            | 15    |
| 0.0036     | 0.0026          | 1.0            | 16    |
| 0.0032     | 0.0023          | 1.0            | 17    |
| 0.0029     | 0.0021          | 1.0            | 18    |
| 0.0027     | 0.0019          | 1.0            | 19    |
| 0.0024     | 0.0017          | 1.0            | 20    |
| 0.0022     | 0.0016          | 1.0            | 21    |
| 0.0020     | 0.0015          | 1.0            | 22    |
| 0.0018     | 0.0013          | 1.0            | 23    |
| 0.0017     | 0.0012          | 1.0            | 24    |
| 0.0016     | 0.0011          | 1.0            | 25    |
| 0.0015     | 0.0011          | 1.0            | 26    |
| 0.0014     | 0.0010          | 1.0            | 27    |


### Framework versions

- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3