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# pijarcandra22/t5Indo2Bali

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: 1.1069
- Validation Loss: 1.5697
- 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 |
|:----------:|:---------------:|:-----:|
| 1.8126     | 1.8072          | 0     |
| 1.8017     | 1.8049          | 1     |
| 1.7984     | 1.8042          | 2     |
| 1.7845     | 1.7983          | 3     |
| 1.7843     | 1.7968          | 4     |
| 1.7812     | 1.7930          | 5     |
| 1.7593     | 1.7946          | 6     |
| 1.7647     | 1.7865          | 7     |
| 1.7710     | 1.7826          | 8     |
| 1.7464     | 1.7852          | 9     |
| 1.7467     | 1.7751          | 10    |
| 1.7380     | 1.7758          | 11    |
| 1.7417     | 1.7761          | 12    |
| 1.7433     | 1.7652          | 13    |
| 1.7306     | 1.7678          | 14    |
| 1.7226     | 1.7649          | 15    |
| 1.7102     | 1.7608          | 16    |
| 1.7125     | 1.7589          | 17    |
| 1.7005     | 1.7572          | 18    |
| 1.6927     | 1.7522          | 19    |
| 1.6859     | 1.7467          | 20    |
| 1.6895     | 1.7454          | 21    |
| 1.6780     | 1.7415          | 22    |
| 1.6807     | 1.7408          | 23    |
| 1.6730     | 1.7376          | 24    |
| 1.6673     | 1.7353          | 25    |
| 1.6648     | 1.7340          | 26    |
| 1.6566     | 1.7328          | 27    |
| 1.6537     | 1.7278          | 28    |
| 1.6508     | 1.7304          | 29    |
| 1.6445     | 1.7267          | 30    |
| 1.6437     | 1.7268          | 31    |
| 1.6345     | 1.7249          | 32    |
| 1.6228     | 1.7192          | 33    |
| 1.6310     | 1.7136          | 34    |
| 1.6236     | 1.7140          | 35    |
| 1.6151     | 1.7158          | 36    |
| 1.6114     | 1.7107          | 37    |
| 1.6076     | 1.7115          | 38    |
| 1.6047     | 1.7066          | 39    |
| 1.5923     | 1.7089          | 40    |
| 1.5897     | 1.7024          | 41    |
| 1.5822     | 1.7000          | 42    |
| 1.5815     | 1.6983          | 43    |
| 1.5854     | 1.6984          | 44    |
| 1.5728     | 1.6962          | 45    |
| 1.5672     | 1.6971          | 46    |
| 1.5735     | 1.6899          | 47    |
| 1.5576     | 1.6894          | 48    |
| 1.5649     | 1.6853          | 49    |
| 1.5572     | 1.6839          | 50    |
| 1.5534     | 1.6813          | 51    |
| 1.5491     | 1.6811          | 52    |
| 1.5487     | 1.6807          | 53    |
| 1.5376     | 1.6763          | 54    |
| 1.5367     | 1.6772          | 55    |
| 1.5242     | 1.6744          | 56    |
| 1.5251     | 1.6687          | 57    |
| 1.5246     | 1.6708          | 58    |
| 1.5260     | 1.6673          | 59    |
| 1.5073     | 1.6699          | 60    |
| 1.5063     | 1.6658          | 61    |
| 1.5238     | 1.6630          | 62    |
| 1.4991     | 1.6612          | 63    |
| 1.4994     | 1.6610          | 64    |
| 1.5001     | 1.6599          | 65    |
| 1.4911     | 1.6612          | 66    |
| 1.4926     | 1.6554          | 67    |
| 1.4852     | 1.6527          | 68    |
| 1.4720     | 1.6554          | 69    |
| 1.4740     | 1.6533          | 70    |
| 1.4759     | 1.6487          | 71    |
| 1.4692     | 1.6450          | 72    |
| 1.4632     | 1.6480          | 73    |
| 1.4664     | 1.6424          | 74    |
| 1.4591     | 1.6436          | 75    |
| 1.4606     | 1.6384          | 76    |
| 1.4487     | 1.6382          | 77    |
| 1.4558     | 1.6375          | 78    |
| 1.4455     | 1.6389          | 79    |
| 1.4396     | 1.6427          | 80    |
| 1.4441     | 1.6363          | 81    |
| 1.4333     | 1.6357          | 82    |
| 1.4414     | 1.6348          | 83    |
| 1.4260     | 1.6319          | 84    |
| 1.4249     | 1.6317          | 85    |
| 1.4166     | 1.6268          | 86    |
| 1.4167     | 1.6301          | 87    |
| 1.4150     | 1.6244          | 88    |
| 1.4061     | 1.6273          | 89    |
| 1.4134     | 1.6260          | 90    |
| 1.4022     | 1.6237          | 91    |
| 1.3949     | 1.6246          | 92    |
| 1.4007     | 1.6231          | 93    |
| 1.3987     | 1.6184          | 94    |
| 1.3919     | 1.6178          | 95    |
| 1.3889     | 1.6178          | 96    |
| 1.3883     | 1.6209          | 97    |
| 1.3756     | 1.6175          | 98    |
| 1.3818     | 1.6139          | 99    |
| 1.3772     | 1.6129          | 100   |
| 1.3726     | 1.6159          | 101   |
| 1.3695     | 1.6158          | 102   |
| 1.3707     | 1.6110          | 103   |
| 1.3555     | 1.6132          | 104   |
| 1.3592     | 1.6085          | 105   |
| 1.3562     | 1.6111          | 106   |
| 1.3475     | 1.6095          | 107   |
| 1.3460     | 1.6100          | 108   |
| 1.3446     | 1.6093          | 109   |
| 1.3436     | 1.6095          | 110   |
| 1.3452     | 1.6068          | 111   |
| 1.3401     | 1.6054          | 112   |
| 1.3378     | 1.6085          | 113   |
| 1.3288     | 1.6056          | 114   |
| 1.3294     | 1.6057          | 115   |
| 1.3227     | 1.6018          | 116   |
| 1.3270     | 1.5989          | 117   |
| 1.3214     | 1.5956          | 118   |
| 1.3187     | 1.5986          | 119   |
| 1.3150     | 1.5986          | 120   |
| 1.3145     | 1.5958          | 121   |
| 1.3159     | 1.5980          | 122   |
| 1.3050     | 1.5978          | 123   |
| 1.3113     | 1.5956          | 124   |
| 1.2932     | 1.5972          | 125   |
| 1.3008     | 1.5927          | 126   |
| 1.2963     | 1.5960          | 127   |
| 1.2799     | 1.5950          | 128   |
| 1.2879     | 1.5918          | 129   |
| 1.2873     | 1.5891          | 130   |
| 1.2868     | 1.5884          | 131   |
| 1.2789     | 1.5922          | 132   |
| 1.2751     | 1.5887          | 133   |
| 1.2780     | 1.5888          | 134   |
| 1.2632     | 1.5913          | 135   |
| 1.2617     | 1.5835          | 136   |
| 1.2681     | 1.5910          | 137   |
| 1.2630     | 1.5893          | 138   |
| 1.2631     | 1.5877          | 139   |
| 1.2540     | 1.5892          | 140   |
| 1.2518     | 1.5812          | 141   |
| 1.2611     | 1.5812          | 142   |
| 1.2561     | 1.5808          | 143   |
| 1.2483     | 1.5757          | 144   |
| 1.2424     | 1.5785          | 145   |
| 1.2366     | 1.5806          | 146   |
| 1.2393     | 1.5801          | 147   |
| 1.2359     | 1.5781          | 148   |
| 1.2256     | 1.5796          | 149   |
| 1.2261     | 1.5818          | 150   |
| 1.2179     | 1.5782          | 151   |
| 1.2321     | 1.5720          | 152   |
| 1.2198     | 1.5744          | 153   |
| 1.2189     | 1.5780          | 154   |
| 1.2301     | 1.5747          | 155   |
| 1.2131     | 1.5776          | 156   |
| 1.2095     | 1.5746          | 157   |
| 1.2134     | 1.5756          | 158   |
| 1.2061     | 1.5761          | 159   |
| 1.2068     | 1.5727          | 160   |
| 1.2061     | 1.5714          | 161   |
| 1.1998     | 1.5756          | 162   |
| 1.1967     | 1.5780          | 163   |
| 1.1940     | 1.5747          | 164   |
| 1.1869     | 1.5713          | 165   |
| 1.1980     | 1.5700          | 166   |
| 1.1958     | 1.5714          | 167   |
| 1.1867     | 1.5666          | 168   |
| 1.1779     | 1.5715          | 169   |
| 1.1789     | 1.5765          | 170   |
| 1.1763     | 1.5742          | 171   |
| 1.1767     | 1.5708          | 172   |
| 1.1840     | 1.5682          | 173   |
| 1.1688     | 1.5747          | 174   |
| 1.1701     | 1.5696          | 175   |
| 1.1739     | 1.5658          | 176   |
| 1.1572     | 1.5688          | 177   |
| 1.1593     | 1.5659          | 178   |
| 1.1591     | 1.5684          | 179   |
| 1.1581     | 1.5644          | 180   |
| 1.1635     | 1.5655          | 181   |
| 1.1538     | 1.5662          | 182   |
| 1.1455     | 1.5666          | 183   |
| 1.1442     | 1.5650          | 184   |
| 1.1398     | 1.5668          | 185   |
| 1.1408     | 1.5712          | 186   |
| 1.1364     | 1.5679          | 187   |
| 1.1348     | 1.5653          | 188   |
| 1.1358     | 1.5704          | 189   |
| 1.1355     | 1.5652          | 190   |
| 1.1278     | 1.5650          | 191   |
| 1.1260     | 1.5697          | 192   |
| 1.1257     | 1.5686          | 193   |
| 1.1265     | 1.5712          | 194   |
| 1.1248     | 1.5625          | 195   |
| 1.1220     | 1.5704          | 196   |
| 1.1202     | 1.5666          | 197   |
| 1.1114     | 1.5653          | 198   |
| 1.1069     | 1.5697          | 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/t5Indo2Bali", "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