---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ratish/DBERT_CleanDesc_COLLISION_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_COLLISION_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: 0.1992
- Validation Loss: 1.6291
- Train Accuracy: 0.6154
- 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': 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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 1.6309     | 1.7295          | 0.3077         | 0     |
| 1.4522     | 1.7291          | 0.3077         | 1     |
| 1.3637     | 1.6656          | 0.3590         | 2     |
| 1.2159     | 1.5797          | 0.4103         | 3     |
| 1.0494     | 1.4799          | 0.4872         | 4     |
| 0.8847     | 1.4288          | 0.5385         | 5     |
| 0.7629     | 1.4239          | 0.5128         | 6     |
| 0.6739     | 1.4484          | 0.5128         | 7     |
| 0.5598     | 1.4533          | 0.6154         | 8     |
| 0.4606     | 1.4160          | 0.6154         | 9     |
| 0.3736     | 1.4206          | 0.5897         | 10    |
| 0.3065     | 1.5229          | 0.5897         | 11    |
| 0.2580     | 1.6168          | 0.5641         | 12    |
| 0.2342     | 1.5924          | 0.6410         | 13    |
| 0.1992     | 1.6291          | 0.6154         | 14    |


### Framework versions

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