---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ratish/DBERT_ZS_CleanCollision_v5
  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_v5

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: 0.0711
- Validation Loss: 1.0938
- Train Accuracy: 0.7241
- 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': 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.0564     | 1.0989          | 0.3448         | 0     |
| 0.9868     | 1.0396          | 0.3793         | 1     |
| 0.8587     | 0.9688          | 0.3793         | 2     |
| 0.6715     | 0.8894          | 0.5862         | 3     |
| 0.4483     | 1.1789          | 0.5172         | 4     |
| 0.3122     | 1.0062          | 0.6207         | 5     |
| 0.1955     | 0.6730          | 0.7241         | 6     |
| 0.1566     | 0.8331          | 0.7241         | 7     |
| 0.1091     | 1.1390          | 0.6207         | 8     |
| 0.0711     | 1.0938          | 0.7241         | 9     |


### Framework versions

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