---
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: 1.8016
- Validation Loss: 1.6860
- Epoch: 92

## 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    |
| 2.5022     | 2.2569          | 22    |
| 2.4834     | 2.2410          | 23    |
| 2.4641     | 2.2220          | 24    |
| 2.4443     | 2.2091          | 25    |
| 2.4267     | 2.1948          | 26    |
| 2.4129     | 2.1796          | 27    |
| 2.3937     | 2.1657          | 28    |
| 2.3782     | 2.1523          | 29    |
| 2.3616     | 2.1385          | 30    |
| 2.3471     | 2.1267          | 31    |
| 2.3351     | 2.1110          | 32    |
| 2.3184     | 2.0988          | 33    |
| 2.3047     | 2.0871          | 34    |
| 2.2920     | 2.0768          | 35    |
| 2.2767     | 2.0649          | 36    |
| 2.2651     | 2.0546          | 37    |
| 2.2526     | 2.0445          | 38    |
| 2.2388     | 2.0333          | 39    |
| 2.2264     | 2.0234          | 40    |
| 2.2157     | 2.0165          | 41    |
| 2.2050     | 2.0049          | 42    |
| 2.1906     | 1.9946          | 43    |
| 2.1824     | 1.9845          | 44    |
| 2.1673     | 1.9762          | 45    |
| 2.1559     | 1.9679          | 46    |
| 2.1455     | 1.9608          | 47    |
| 2.1377     | 1.9528          | 48    |
| 2.1279     | 1.9429          | 49    |
| 2.1176     | 1.9356          | 50    |
| 2.1056     | 1.9267          | 51    |
| 2.0979     | 1.9174          | 52    |
| 2.0882     | 1.9087          | 53    |
| 2.0802     | 1.8995          | 54    |
| 2.0668     | 1.8947          | 55    |
| 2.0597     | 1.8880          | 56    |
| 2.0484     | 1.8779          | 57    |
| 2.0405     | 1.8735          | 58    |
| 2.0335     | 1.8676          | 59    |
| 2.0254     | 1.8603          | 60    |
| 2.0147     | 1.8530          | 61    |
| 2.0078     | 1.8459          | 62    |
| 1.9984     | 1.8403          | 63    |
| 1.9902     | 1.8338          | 64    |
| 1.9824     | 1.8264          | 65    |
| 1.9768     | 1.8231          | 66    |
| 1.9679     | 1.8158          | 67    |
| 1.9597     | 1.8104          | 68    |
| 1.9531     | 1.8026          | 69    |
| 1.9460     | 1.7987          | 70    |
| 1.9416     | 1.7929          | 71    |
| 1.9291     | 1.7876          | 72    |
| 1.9245     | 1.7807          | 73    |
| 1.9143     | 1.7788          | 74    |
| 1.9088     | 1.7717          | 75    |
| 1.9006     | 1.7643          | 76    |
| 1.8960     | 1.7587          | 77    |
| 1.8901     | 1.7528          | 78    |
| 1.8808     | 1.7477          | 79    |
| 1.8740     | 1.7436          | 80    |
| 1.8689     | 1.7376          | 81    |
| 1.8628     | 1.7320          | 82    |
| 1.8533     | 1.7312          | 83    |
| 1.8486     | 1.7240          | 84    |
| 1.8428     | 1.7186          | 85    |
| 1.8351     | 1.7141          | 86    |
| 1.8316     | 1.7106          | 87    |
| 1.8234     | 1.7045          | 88    |
| 1.8173     | 1.6976          | 89    |
| 1.8109     | 1.6959          | 90    |
| 1.8059     | 1.6924          | 91    |
| 1.8016     | 1.6860          | 92    |


### Framework versions

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