---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: PromptGenerator_5_topic_finetuned
  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. -->

# PromptGenerator_5_topic_finetuned

This model is a fine-tuned version of [kmkarakaya/turkishReviews-ds](https://huggingface.co/kmkarakaya/turkishReviews-ds) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 1.6861
- Train Sparse Categorical Accuracy: 0.8150
- Validation Loss: 1.9777
- Validation Sparse Categorical Accuracy: 0.7250
- Epoch: 4

## 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', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 3.0394     | 0.5171                            | 2.7152          | 0.5841                                 | 0     |
| 2.5336     | 0.6247                            | 2.4440          | 0.6318                                 | 1     |
| 2.2002     | 0.6958                            | 2.2557          | 0.6659                                 | 2     |
| 1.9241     | 0.7608                            | 2.1059          | 0.6932                                 | 3     |
| 1.6861     | 0.8150                            | 1.9777          | 0.7250                                 | 4     |


### Framework versions

- Transformers 4.21.1
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1