---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: pijarcandra22/t5Indo2Jawa
  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. -->

# pijarcandra22/t5Indo2Jawa

This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.5224
- Validation Loss: 2.2750
- Epoch: 21

## 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.5149     | 3.1567          | 0     |
| 3.3816     | 3.0397          | 1     |
| 3.2812     | 2.9518          | 2     |
| 3.1977     | 2.8751          | 3     |
| 3.1223     | 2.8078          | 4     |
| 3.0599     | 2.7507          | 5     |
| 3.0019     | 2.6979          | 6     |
| 2.9517     | 2.6513          | 7     |
| 2.9034     | 2.6121          | 8     |
| 2.8638     | 2.5756          | 9     |
| 2.8232     | 2.5391          | 10    |
| 2.7856     | 2.5089          | 11    |
| 2.7541     | 2.4786          | 12    |
| 2.7219     | 2.4499          | 13    |
| 2.6935     | 2.4256          | 14    |
| 2.6658     | 2.4010          | 15    |
| 2.6389     | 2.3762          | 16    |
| 2.6143     | 2.3550          | 17    |
| 2.5899     | 2.3313          | 18    |
| 2.5665     | 2.3156          | 19    |
| 2.5445     | 2.2939          | 20    |
| 2.5224     | 2.2750          | 21    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0