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# 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: 1.3740
- Validation Loss: 1.4176
- Epoch: 199

## 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    |
| 1.7922     | 1.6802          | 93    |
| 1.7887     | 1.6778          | 94    |
| 1.7832     | 1.6716          | 95    |
| 1.7761     | 1.6688          | 96    |
| 1.7724     | 1.6653          | 97    |
| 1.7662     | 1.6582          | 98    |
| 1.7607     | 1.6571          | 99    |
| 1.7549     | 1.6542          | 100   |
| 1.7483     | 1.6497          | 101   |
| 1.7454     | 1.6435          | 102   |
| 1.7400     | 1.6407          | 103   |
| 1.7318     | 1.6363          | 104   |
| 1.7266     | 1.6327          | 105   |
| 1.7234     | 1.6286          | 106   |
| 1.7210     | 1.6267          | 107   |
| 1.7109     | 1.6207          | 108   |
| 1.7079     | 1.6183          | 109   |
| 1.7026     | 1.6162          | 110   |
| 1.6989     | 1.6137          | 111   |
| 1.6925     | 1.6074          | 112   |
| 1.6880     | 1.6051          | 113   |
| 1.6823     | 1.6021          | 114   |
| 1.6780     | 1.5969          | 115   |
| 1.6737     | 1.5960          | 116   |
| 1.6659     | 1.5937          | 117   |
| 1.6603     | 1.5872          | 118   |
| 1.6586     | 1.5870          | 119   |
| 1.6550     | 1.5813          | 120   |
| 1.6506     | 1.5788          | 121   |
| 1.6432     | 1.5771          | 122   |
| 1.6408     | 1.5721          | 123   |
| 1.6377     | 1.5729          | 124   |
| 1.6307     | 1.5693          | 125   |
| 1.6268     | 1.5650          | 126   |
| 1.6227     | 1.5607          | 127   |
| 1.6180     | 1.5618          | 128   |
| 1.6151     | 1.5590          | 129   |
| 1.6101     | 1.5534          | 130   |
| 1.6056     | 1.5505          | 131   |
| 1.6034     | 1.5470          | 132   |
| 1.5971     | 1.5443          | 133   |
| 1.5926     | 1.5431          | 134   |
| 1.5873     | 1.5421          | 135   |
| 1.5850     | 1.5378          | 136   |
| 1.5807     | 1.5334          | 137   |
| 1.5771     | 1.5335          | 138   |
| 1.5734     | 1.5309          | 139   |
| 1.5694     | 1.5288          | 140   |
| 1.5642     | 1.5273          | 141   |
| 1.5610     | 1.5215          | 142   |
| 1.5568     | 1.5217          | 143   |
| 1.5555     | 1.5171          | 144   |
| 1.5517     | 1.5170          | 145   |
| 1.5471     | 1.5148          | 146   |
| 1.5426     | 1.5120          | 147   |
| 1.5376     | 1.5102          | 148   |
| 1.5370     | 1.5081          | 149   |
| 1.5317     | 1.5070          | 150   |
| 1.5272     | 1.5029          | 151   |
| 1.5257     | 1.5025          | 152   |
| 1.5205     | 1.4997          | 153   |
| 1.5180     | 1.4954          | 154   |
| 1.5112     | 1.4932          | 155   |
| 1.5117     | 1.4920          | 156   |
| 1.5070     | 1.4890          | 157   |
| 1.5050     | 1.4881          | 158   |
| 1.4984     | 1.4870          | 159   |
| 1.4964     | 1.4843          | 160   |
| 1.4920     | 1.4833          | 161   |
| 1.4879     | 1.4808          | 162   |
| 1.4838     | 1.4768          | 163   |
| 1.4854     | 1.4756          | 164   |
| 1.4784     | 1.4733          | 165   |
| 1.4757     | 1.4724          | 166   |
| 1.4733     | 1.4697          | 167   |
| 1.4704     | 1.4678          | 168   |
| 1.4660     | 1.4648          | 169   |
| 1.4618     | 1.4660          | 170   |
| 1.4591     | 1.4606          | 171   |
| 1.4554     | 1.4626          | 172   |
| 1.4533     | 1.4595          | 173   |
| 1.4492     | 1.4583          | 174   |
| 1.4471     | 1.4539          | 175   |
| 1.4410     | 1.4548          | 176   |
| 1.4387     | 1.4507          | 177   |
| 1.4370     | 1.4484          | 178   |
| 1.4336     | 1.4482          | 179   |
| 1.4301     | 1.4468          | 180   |
| 1.4300     | 1.4441          | 181   |
| 1.4246     | 1.4429          | 182   |
| 1.4221     | 1.4440          | 183   |
| 1.4171     | 1.4418          | 184   |
| 1.4150     | 1.4359          | 185   |
| 1.4131     | 1.4377          | 186   |
| 1.4110     | 1.4358          | 187   |
| 1.4081     | 1.4321          | 188   |
| 1.4025     | 1.4333          | 189   |
| 1.4010     | 1.4293          | 190   |
| 1.3966     | 1.4288          | 191   |
| 1.3949     | 1.4293          | 192   |
| 1.3921     | 1.4252          | 193   |
| 1.3914     | 1.4253          | 194   |
| 1.3866     | 1.4240          | 195   |
| 1.3832     | 1.4208          | 196   |
| 1.3818     | 1.4221          | 197   |
| 1.3765     | 1.4185          | 198   |
| 1.3740     | 1.4176          | 199   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "base_model": "t5-small", "model-index": [{"name": "pijarcandra22/t5Indo2Jawa", "results": []}]}
transformers tf t5 text2text-generation generated_from_keras_callback base_model:t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us