
<!-- 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/t5Jawa2Indo

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: 0.9572
- Validation Loss: 1.1659
- Epoch: 299

## 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 |
|:----------:|:---------------:|:-----:|
| 3.8958     | 3.3598          | 0     |
| 3.4684     | 3.0863          | 1     |
| 3.2505     | 2.9092          | 2     |
| 3.0952     | 2.7813          | 3     |
| 2.9749     | 2.6834          | 4     |
| 2.8813     | 2.6016          | 5     |
| 2.8008     | 2.5321          | 6     |
| 2.7323     | 2.4726          | 7     |
| 2.6741     | 2.4187          | 8     |
| 2.6219     | 2.3724          | 9     |
| 2.5735     | 2.3279          | 10    |
| 2.5324     | 2.2918          | 11    |
| 2.4934     | 2.2575          | 12    |
| 2.4570     | 2.2271          | 13    |
| 2.4214     | 2.1950          | 14    |
| 2.3906     | 2.1661          | 15    |
| 2.3628     | 2.1396          | 16    |
| 2.3341     | 2.1168          | 17    |
| 2.3097     | 2.0924          | 18    |
| 2.2824     | 2.0717          | 19    |
| 2.2592     | 2.0504          | 20    |
| 2.2377     | 2.0338          | 21    |
| 2.2139     | 2.0142          | 22    |
| 2.1953     | 1.9946          | 23    |
| 2.1751     | 1.9793          | 24    |
| 2.1572     | 1.9625          | 25    |
| 2.1375     | 1.9471          | 26    |
| 2.1208     | 1.9300          | 27    |
| 2.1063     | 1.9190          | 28    |
| 2.0866     | 1.9050          | 29    |
| 2.0748     | 1.8916          | 30    |
| 2.0568     | 1.8809          | 31    |
| 2.0418     | 1.8682          | 32    |
| 2.0274     | 1.8551          | 33    |
| 2.0139     | 1.8468          | 34    |
| 2.0026     | 1.8347          | 35    |
| 1.9880     | 1.8248          | 36    |
| 1.9746     | 1.8128          | 37    |
| 1.9608     | 1.8056          | 38    |
| 1.9524     | 1.7968          | 39    |
| 1.9414     | 1.7840          | 40    |
| 1.9269     | 1.7764          | 41    |
| 1.9160     | 1.7662          | 42    |
| 1.9041     | 1.7602          | 43    |
| 1.8962     | 1.7503          | 44    |
| 1.8826     | 1.7414          | 45    |
| 1.8737     | 1.7359          | 46    |
| 1.8635     | 1.7273          | 47    |
| 1.8544     | 1.7207          | 48    |
| 1.8476     | 1.7135          | 49    |
| 1.8355     | 1.7051          | 50    |
| 1.8272     | 1.6969          | 51    |
| 1.8178     | 1.6906          | 52    |
| 1.8079     | 1.6862          | 53    |
| 1.7998     | 1.6786          | 54    |
| 1.7939     | 1.6712          | 55    |
| 1.7826     | 1.6628          | 56    |
| 1.7752     | 1.6567          | 57    |
| 1.7675     | 1.6518          | 58    |
| 1.7606     | 1.6464          | 59    |
| 1.7510     | 1.6408          | 60    |
| 1.7456     | 1.6329          | 61    |
| 1.7390     | 1.6284          | 62    |
| 1.7289     | 1.6233          | 63    |
| 1.7183     | 1.6176          | 64    |
| 1.7127     | 1.6125          | 65    |
| 1.7087     | 1.6098          | 66    |
| 1.6990     | 1.5985          | 67    |
| 1.6945     | 1.5934          | 68    |
| 1.6872     | 1.5876          | 69    |
| 1.6795     | 1.5816          | 70    |
| 1.6758     | 1.5778          | 71    |
| 1.6659     | 1.5742          | 72    |
| 1.6603     | 1.5702          | 73    |
| 1.6516     | 1.5618          | 74    |
| 1.6463     | 1.5592          | 75    |
| 1.6400     | 1.5541          | 76    |
| 1.6354     | 1.5484          | 77    |
| 1.6305     | 1.5424          | 78    |
| 1.6217     | 1.5378          | 79    |
| 1.6169     | 1.5338          | 80    |
| 1.6102     | 1.5301          | 81    |
| 1.6070     | 1.5229          | 82    |
| 1.5979     | 1.5195          | 83    |
| 1.5926     | 1.5163          | 84    |
| 1.5875     | 1.5106          | 85    |
| 1.5814     | 1.5075          | 86    |
| 1.5748     | 1.5021          | 87    |
| 1.5672     | 1.4984          | 88    |
| 1.5657     | 1.4945          | 89    |
| 1.5597     | 1.4913          | 90    |
| 1.5530     | 1.4863          | 91    |
| 1.5506     | 1.4821          | 92    |
| 1.5437     | 1.4785          | 93    |
| 1.5405     | 1.4730          | 94    |
| 1.5325     | 1.4678          | 95    |
| 1.5285     | 1.4666          | 96    |
| 1.5233     | 1.4634          | 97    |
| 1.5189     | 1.4580          | 98    |
| 1.5122     | 1.4558          | 99    |
| 1.5078     | 1.4517          | 100   |
| 1.5059     | 1.4471          | 101   |
| 1.4956     | 1.4446          | 102   |
| 1.4944     | 1.4396          | 103   |
| 1.4881     | 1.4371          | 104   |
| 1.4851     | 1.4334          | 105   |
| 1.4763     | 1.4295          | 106   |
| 1.4725     | 1.4273          | 107   |
| 1.4686     | 1.4243          | 108   |
| 1.4663     | 1.4196          | 109   |
| 1.4588     | 1.4180          | 110   |
| 1.4558     | 1.4152          | 111   |
| 1.4525     | 1.4127          | 112   |
| 1.4465     | 1.4085          | 113   |
| 1.4431     | 1.4052          | 114   |
| 1.4386     | 1.4025          | 115   |
| 1.4343     | 1.4000          | 116   |
| 1.4306     | 1.3969          | 117   |
| 1.4259     | 1.3925          | 118   |
| 1.4192     | 1.3919          | 119   |
| 1.4165     | 1.3886          | 120   |
| 1.4109     | 1.3857          | 121   |
| 1.4093     | 1.3844          | 122   |
| 1.4058     | 1.3797          | 123   |
| 1.4003     | 1.3779          | 124   |
| 1.3992     | 1.3733          | 125   |
| 1.3898     | 1.3721          | 126   |
| 1.3877     | 1.3692          | 127   |
| 1.3845     | 1.3681          | 128   |
| 1.3821     | 1.3665          | 129   |
| 1.3767     | 1.3652          | 130   |
| 1.3720     | 1.3600          | 131   |
| 1.3707     | 1.3572          | 132   |
| 1.3674     | 1.3546          | 133   |
| 1.3628     | 1.3550          | 134   |
| 1.3582     | 1.3510          | 135   |
| 1.3548     | 1.3484          | 136   |
| 1.3518     | 1.3481          | 137   |
| 1.3490     | 1.3467          | 138   |
| 1.3463     | 1.3423          | 139   |
| 1.3411     | 1.3401          | 140   |
| 1.3367     | 1.3387          | 141   |
| 1.3332     | 1.3371          | 142   |
| 1.3313     | 1.3341          | 143   |
| 1.3285     | 1.3304          | 144   |
| 1.3235     | 1.3302          | 145   |
| 1.3203     | 1.3292          | 146   |
| 1.3186     | 1.3259          | 147   |
| 1.3132     | 1.3230          | 148   |
| 1.3106     | 1.3233          | 149   |
| 1.3083     | 1.3169          | 150   |
| 1.3011     | 1.3179          | 151   |
| 1.2986     | 1.3151          | 152   |
| 1.2975     | 1.3150          | 153   |
| 1.2905     | 1.3124          | 154   |
| 1.2887     | 1.3096          | 155   |
| 1.2862     | 1.3105          | 156   |
| 1.2831     | 1.3064          | 157   |
| 1.2796     | 1.3051          | 158   |
| 1.2777     | 1.3024          | 159   |
| 1.2758     | 1.2993          | 160   |
| 1.2694     | 1.2997          | 161   |
| 1.2681     | 1.2974          | 162   |
| 1.2626     | 1.2935          | 163   |
| 1.2617     | 1.2946          | 164   |
| 1.2592     | 1.2928          | 165   |
| 1.2562     | 1.2899          | 166   |
| 1.2520     | 1.2890          | 167   |
| 1.2488     | 1.2876          | 168   |
| 1.2468     | 1.2848          | 169   |
| 1.2450     | 1.2840          | 170   |
| 1.2388     | 1.2861          | 171   |
| 1.2384     | 1.2815          | 172   |
| 1.2331     | 1.2808          | 173   |
| 1.2328     | 1.2774          | 174   |
| 1.2299     | 1.2770          | 175   |
| 1.2253     | 1.2752          | 176   |
| 1.2251     | 1.2740          | 177   |
| 1.2188     | 1.2722          | 178   |
| 1.2167     | 1.2706          | 179   |
| 1.2141     | 1.2679          | 180   |
| 1.2125     | 1.2671          | 181   |
| 1.2080     | 1.2674          | 182   |
| 1.2049     | 1.2665          | 183   |
| 1.2021     | 1.2635          | 184   |
| 1.2013     | 1.2629          | 185   |
| 1.1975     | 1.2599          | 186   |
| 1.1946     | 1.2593          | 187   |
| 1.1939     | 1.2599          | 188   |
| 1.1897     | 1.2560          | 189   |
| 1.1879     | 1.2569          | 190   |
| 1.1841     | 1.2539          | 191   |
| 1.1829     | 1.2540          | 192   |
| 1.1804     | 1.2538          | 193   |
| 1.1759     | 1.2513          | 194   |
| 1.1745     | 1.2480          | 195   |
| 1.1690     | 1.2483          | 196   |
| 1.1686     | 1.2458          | 197   |
| 1.1647     | 1.2450          | 198   |
| 1.1628     | 1.2457          | 199   |
| 1.1624     | 1.2461          | 200   |
| 1.1584     | 1.2429          | 201   |
| 1.1563     | 1.2417          | 202   |
| 1.1543     | 1.2407          | 203   |
| 1.1489     | 1.2391          | 204   |
| 1.1464     | 1.2422          | 205   |
| 1.1482     | 1.2384          | 206   |
| 1.1446     | 1.2355          | 207   |
| 1.1425     | 1.2351          | 208   |
| 1.1373     | 1.2343          | 209   |
| 1.1378     | 1.2327          | 210   |
| 1.1362     | 1.2311          | 211   |
| 1.1331     | 1.2304          | 212   |
| 1.1315     | 1.2279          | 213   |
| 1.1265     | 1.2290          | 214   |
| 1.1254     | 1.2284          | 215   |
| 1.1220     | 1.2276          | 216   |
| 1.1208     | 1.2230          | 217   |
| 1.1218     | 1.2220          | 218   |
| 1.1140     | 1.2222          | 219   |
| 1.1115     | 1.2205          | 220   |
| 1.1120     | 1.2223          | 221   |
| 1.1081     | 1.2213          | 222   |
| 1.1059     | 1.2190          | 223   |
| 1.1025     | 1.2186          | 224   |
| 1.1031     | 1.2182          | 225   |
| 1.0996     | 1.2155          | 226   |
| 1.0972     | 1.2144          | 227   |
| 1.0953     | 1.2136          | 228   |
| 1.0929     | 1.2126          | 229   |
| 1.0893     | 1.2153          | 230   |
| 1.0868     | 1.2147          | 231   |
| 1.0877     | 1.2114          | 232   |
| 1.0834     | 1.2118          | 233   |
| 1.0815     | 1.2103          | 234   |
| 1.0802     | 1.2096          | 235   |
| 1.0771     | 1.2110          | 236   |
| 1.0740     | 1.2087          | 237   |
| 1.0735     | 1.2058          | 238   |
| 1.0731     | 1.2077          | 239   |
| 1.0693     | 1.2051          | 240   |
| 1.0667     | 1.2055          | 241   |
| 1.0662     | 1.2034          | 242   |
| 1.0659     | 1.2028          | 243   |
| 1.0619     | 1.2009          | 244   |
| 1.0601     | 1.2020          | 245   |
| 1.0578     | 1.1984          | 246   |
| 1.0541     | 1.2002          | 247   |
| 1.0524     | 1.1992          | 248   |
| 1.0474     | 1.1996          | 249   |
| 1.0493     | 1.1975          | 250   |
| 1.0466     | 1.1986          | 251   |
| 1.0454     | 1.1955          | 252   |
| 1.0448     | 1.1940          | 253   |
| 1.0388     | 1.1944          | 254   |
| 1.0373     | 1.1930          | 255   |
| 1.0345     | 1.1956          | 256   |
| 1.0330     | 1.1915          | 257   |
| 1.0329     | 1.1902          | 258   |
| 1.0310     | 1.1923          | 259   |
| 1.0277     | 1.1905          | 260   |
| 1.0282     | 1.1890          | 261   |
| 1.0229     | 1.1895          | 262   |
| 1.0225     | 1.1888          | 263   |
| 1.0227     | 1.1877          | 264   |
| 1.0207     | 1.1845          | 265   |
| 1.0165     | 1.1870          | 266   |
| 1.0143     | 1.1850          | 267   |
| 1.0133     | 1.1838          | 268   |
| 1.0107     | 1.1851          | 269   |
| 1.0097     | 1.1852          | 270   |
| 1.0082     | 1.1829          | 271   |
| 1.0050     | 1.1824          | 272   |
| 1.0032     | 1.1834          | 273   |
| 1.0017     | 1.1806          | 274   |
| 1.0017     | 1.1805          | 275   |
| 0.9989     | 1.1814          | 276   |
| 0.9985     | 1.1779          | 277   |
| 0.9947     | 1.1782          | 278   |
| 0.9940     | 1.1776          | 279   |
| 0.9921     | 1.1779          | 280   |
| 0.9909     | 1.1788          | 281   |
| 0.9876     | 1.1764          | 282   |
| 0.9867     | 1.1763          | 283   |
| 0.9832     | 1.1762          | 284   |
| 0.9795     | 1.1743          | 285   |
| 0.9791     | 1.1762          | 286   |
| 0.9772     | 1.1724          | 287   |
| 0.9770     | 1.1729          | 288   |
| 0.9754     | 1.1757          | 289   |
| 0.9730     | 1.1711          | 290   |
| 0.9707     | 1.1734          | 291   |
| 0.9700     | 1.1732          | 292   |
| 0.9683     | 1.1699          | 293   |
| 0.9653     | 1.1705          | 294   |
| 0.9660     | 1.1706          | 295   |
| 0.9626     | 1.1679          | 296   |
| 0.9625     | 1.1666          | 297   |
| 0.9592     | 1.1693          | 298   |
| 0.9572     | 1.1659          | 299   |


### 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/t5Jawa2Indo", "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