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# t5-small-finetuned-text2log-finetuned-nl-to-fol-finetuned-nl-to-fol

This model is a fine-tuned version of [anki08/t5-small-finetuned-text2log-finetuned-nl-to-fol](https://huggingface.co/anki08/t5-small-finetuned-text2log-finetuned-nl-to-fol) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0117
- Bleu: 26.9533
- Gen Len: 18.7206

## 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:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 17   | 0.6271          | 21.6075 | 18.6912 |
| No log        | 2.0   | 34   | 0.4985          | 21.6117 | 18.6912 |
| No log        | 3.0   | 51   | 0.4213          | 22.1637 | 18.6912 |
| No log        | 4.0   | 68   | 0.3745          | 22.4107 | 18.6912 |
| No log        | 5.0   | 85   | 0.3410          | 22.8843 | 18.6912 |
| No log        | 6.0   | 102  | 0.3200          | 22.8262 | 18.6912 |
| No log        | 7.0   | 119  | 0.2925          | 22.6535 | 18.6912 |
| No log        | 8.0   | 136  | 0.2790          | 22.733  | 18.6912 |
| No log        | 9.0   | 153  | 0.2696          | 23.0984 | 18.6912 |
| No log        | 10.0  | 170  | 0.2550          | 22.7433 | 18.6912 |
| No log        | 11.0  | 187  | 0.2449          | 22.959  | 18.6912 |
| No log        | 12.0  | 204  | 0.2301          | 23.2707 | 18.6912 |
| No log        | 13.0  | 221  | 0.2222          | 23.1237 | 18.6912 |
| No log        | 14.0  | 238  | 0.2098          | 23.2703 | 18.6912 |
| No log        | 15.0  | 255  | 0.2010          | 23.406  | 18.6912 |
| No log        | 16.0  | 272  | 0.1926          | 23.5024 | 18.6912 |
| No log        | 17.0  | 289  | 0.1871          | 23.644  | 18.6912 |
| No log        | 18.0  | 306  | 0.1801          | 23.8176 | 18.6912 |
| No log        | 19.0  | 323  | 0.1714          | 23.5624 | 18.6912 |
| No log        | 20.0  | 340  | 0.1640          | 23.8308 | 18.6912 |
| No log        | 21.0  | 357  | 0.1582          | 23.7387 | 18.6912 |
| No log        | 22.0  | 374  | 0.1532          | 23.4223 | 18.6912 |
| No log        | 23.0  | 391  | 0.1493          | 23.4963 | 18.6912 |
| No log        | 24.0  | 408  | 0.1469          | 23.4319 | 18.6912 |
| No log        | 25.0  | 425  | 0.1408          | 23.7634 | 18.6912 |
| No log        | 26.0  | 442  | 0.1367          | 23.6347 | 18.6912 |
| No log        | 27.0  | 459  | 0.1316          | 23.6694 | 18.6912 |
| No log        | 28.0  | 476  | 0.1274          | 23.9273 | 18.6912 |
| No log        | 29.0  | 493  | 0.1237          | 24.0772 | 18.6912 |
| 0.3817        | 30.0  | 510  | 0.1190          | 24.3082 | 18.6912 |
| 0.3817        | 31.0  | 527  | 0.1172          | 24.4804 | 18.6691 |
| 0.3817        | 32.0  | 544  | 0.1137          | 24.2785 | 18.6691 |
| 0.3817        | 33.0  | 561  | 0.1107          | 24.2177 | 18.6912 |
| 0.3817        | 34.0  | 578  | 0.1060          | 23.6294 | 18.6912 |
| 0.3817        | 35.0  | 595  | 0.1019          | 24.2786 | 18.6912 |
| 0.3817        | 36.0  | 612  | 0.0991          | 24.4832 | 18.6691 |
| 0.3817        | 37.0  | 629  | 0.0976          | 24.7323 | 18.6691 |
| 0.3817        | 38.0  | 646  | 0.0966          | 24.5546 | 18.6691 |
| 0.3817        | 39.0  | 663  | 0.0951          | 24.6238 | 18.6691 |
| 0.3817        | 40.0  | 680  | 0.0918          | 24.4027 | 18.6691 |
| 0.3817        | 41.0  | 697  | 0.0892          | 24.5354 | 18.6691 |
| 0.3817        | 42.0  | 714  | 0.0866          | 24.427  | 18.6691 |
| 0.3817        | 43.0  | 731  | 0.0851          | 24.0645 | 18.6691 |
| 0.3817        | 44.0  | 748  | 0.0836          | 24.2317 | 18.6691 |
| 0.3817        | 45.0  | 765  | 0.0816          | 24.4578 | 18.6691 |
| 0.3817        | 46.0  | 782  | 0.0799          | 24.5216 | 18.6691 |
| 0.3817        | 47.0  | 799  | 0.0774          | 24.7976 | 18.6691 |
| 0.3817        | 48.0  | 816  | 0.0755          | 24.6819 | 18.6691 |
| 0.3817        | 49.0  | 833  | 0.0725          | 24.7607 | 18.6691 |
| 0.3817        | 50.0  | 850  | 0.0720          | 24.9414 | 18.6691 |
| 0.3817        | 51.0  | 867  | 0.0708          | 24.6746 | 18.6691 |
| 0.3817        | 52.0  | 884  | 0.0694          | 24.791  | 18.6691 |
| 0.3817        | 53.0  | 901  | 0.0667          | 24.7417 | 18.6691 |
| 0.3817        | 54.0  | 918  | 0.0657          | 24.8431 | 18.6691 |
| 0.3817        | 55.0  | 935  | 0.0645          | 25.0305 | 18.6691 |
| 0.3817        | 56.0  | 952  | 0.0639          | 24.986  | 18.6691 |
| 0.3817        | 57.0  | 969  | 0.0615          | 24.986  | 18.6691 |
| 0.3817        | 58.0  | 986  | 0.0603          | 25.0536 | 18.6691 |
| 0.2006        | 59.0  | 1003 | 0.0587          | 25.014  | 18.6691 |
| 0.2006        | 60.0  | 1020 | 0.0576          | 25.0981 | 18.6691 |
| 0.2006        | 61.0  | 1037 | 0.0573          | 25.0262 | 18.6691 |
| 0.2006        | 62.0  | 1054 | 0.0548          | 25.0514 | 18.6691 |
| 0.2006        | 63.0  | 1071 | 0.0545          | 25.036  | 18.6691 |
| 0.2006        | 64.0  | 1088 | 0.0526          | 25.2406 | 18.6691 |
| 0.2006        | 65.0  | 1105 | 0.0511          | 25.276  | 18.6691 |
| 0.2006        | 66.0  | 1122 | 0.0511          | 25.2682 | 18.6691 |
| 0.2006        | 67.0  | 1139 | 0.0504          | 25.1104 | 18.6691 |
| 0.2006        | 68.0  | 1156 | 0.0513          | 25.2775 | 18.6691 |
| 0.2006        | 69.0  | 1173 | 0.0479          | 25.5063 | 18.6691 |
| 0.2006        | 70.0  | 1190 | 0.0470          | 25.4453 | 18.6691 |
| 0.2006        | 71.0  | 1207 | 0.0468          | 25.4056 | 18.6691 |
| 0.2006        | 72.0  | 1224 | 0.0451          | 25.4968 | 18.6691 |
| 0.2006        | 73.0  | 1241 | 0.0441          | 25.6183 | 18.6691 |
| 0.2006        | 74.0  | 1258 | 0.0432          | 25.6308 | 18.6691 |
| 0.2006        | 75.0  | 1275 | 0.0428          | 25.4817 | 18.6691 |
| 0.2006        | 76.0  | 1292 | 0.0417          | 25.6171 | 18.6691 |
| 0.2006        | 77.0  | 1309 | 0.0414          | 25.4539 | 18.6691 |
| 0.2006        | 78.0  | 1326 | 0.0413          | 25.4539 | 18.6691 |
| 0.2006        | 79.0  | 1343 | 0.0399          | 25.3733 | 18.6691 |
| 0.2006        | 80.0  | 1360 | 0.0393          | 25.6878 | 18.6691 |
| 0.2006        | 81.0  | 1377 | 0.0391          | 25.6461 | 18.6691 |
| 0.2006        | 82.0  | 1394 | 0.0384          | 25.8403 | 18.6691 |
| 0.2006        | 83.0  | 1411 | 0.0381          | 25.9332 | 18.6691 |
| 0.2006        | 84.0  | 1428 | 0.0374          | 25.9369 | 18.6691 |
| 0.2006        | 85.0  | 1445 | 0.0371          | 25.8831 | 18.6691 |
| 0.2006        | 86.0  | 1462 | 0.0369          | 25.7971 | 18.6691 |
| 0.2006        | 87.0  | 1479 | 0.0364          | 25.8831 | 18.6691 |
| 0.2006        | 88.0  | 1496 | 0.0353          | 25.918  | 18.6691 |
| 0.1412        | 89.0  | 1513 | 0.0347          | 26.0189 | 18.6691 |
| 0.1412        | 90.0  | 1530 | 0.0342          | 25.9848 | 18.6691 |
| 0.1412        | 91.0  | 1547 | 0.0338          | 25.9848 | 18.6691 |
| 0.1412        | 92.0  | 1564 | 0.0326          | 25.9451 | 18.6691 |
| 0.1412        | 93.0  | 1581 | 0.0328          | 26.1168 | 18.6691 |
| 0.1412        | 94.0  | 1598 | 0.0321          | 26.1039 | 18.6691 |
| 0.1412        | 95.0  | 1615 | 0.0318          | 26.1391 | 18.6691 |
| 0.1412        | 96.0  | 1632 | 0.0329          | 26.1391 | 18.6691 |
| 0.1412        | 97.0  | 1649 | 0.0299          | 26.1745 | 18.6691 |
| 0.1412        | 98.0  | 1666 | 0.0303          | 26.1917 | 18.6691 |
| 0.1412        | 99.0  | 1683 | 0.0290          | 26.0001 | 18.6691 |
| 0.1412        | 100.0 | 1700 | 0.0311          | 26.0437 | 18.6691 |
| 0.1412        | 101.0 | 1717 | 0.0280          | 26.1231 | 18.6691 |
| 0.1412        | 102.0 | 1734 | 0.0288          | 26.2359 | 18.6691 |
| 0.1412        | 103.0 | 1751 | 0.0279          | 26.2359 | 18.6691 |
| 0.1412        | 104.0 | 1768 | 0.0285          | 26.2976 | 18.6691 |
| 0.1412        | 105.0 | 1785 | 0.0263          | 26.3152 | 18.6691 |
| 0.1412        | 106.0 | 1802 | 0.0259          | 26.3548 | 18.6691 |
| 0.1412        | 107.0 | 1819 | 0.0255          | 26.3548 | 18.6691 |
| 0.1412        | 108.0 | 1836 | 0.0253          | 26.3548 | 18.6691 |
| 0.1412        | 109.0 | 1853 | 0.0241          | 26.377  | 18.6691 |
| 0.1412        | 110.0 | 1870 | 0.0247          | 26.3548 | 18.6691 |
| 0.1412        | 111.0 | 1887 | 0.0234          | 26.3901 | 18.6691 |
| 0.1412        | 112.0 | 1904 | 0.0224          | 26.4917 | 18.6691 |
| 0.1412        | 113.0 | 1921 | 0.0220          | 26.4297 | 18.6691 |
| 0.1412        | 114.0 | 1938 | 0.0223          | 26.3548 | 18.6691 |
| 0.1412        | 115.0 | 1955 | 0.0215          | 26.3548 | 18.6691 |
| 0.1412        | 116.0 | 1972 | 0.0211          | 26.3548 | 18.6691 |
| 0.1412        | 117.0 | 1989 | 0.0210          | 26.3548 | 18.6691 |
| 0.1097        | 118.0 | 2006 | 0.0204          | 26.3944 | 18.6691 |
| 0.1097        | 119.0 | 2023 | 0.0204          | 26.3944 | 18.6691 |
| 0.1097        | 120.0 | 2040 | 0.0200          | 26.3944 | 18.6691 |
| 0.1097        | 121.0 | 2057 | 0.0201          | 26.3944 | 18.6691 |
| 0.1097        | 122.0 | 2074 | 0.0196          | 26.3944 | 18.6691 |
| 0.1097        | 123.0 | 2091 | 0.0197          | 26.434  | 18.6691 |
| 0.1097        | 124.0 | 2108 | 0.0189          | 26.434  | 18.6691 |
| 0.1097        | 125.0 | 2125 | 0.0191          | 26.434  | 18.6691 |
| 0.1097        | 126.0 | 2142 | 0.0185          | 26.434  | 18.6691 |
| 0.1097        | 127.0 | 2159 | 0.0185          | 26.496  | 18.6691 |
| 0.1097        | 128.0 | 2176 | 0.0188          | 26.496  | 18.6691 |
| 0.1097        | 129.0 | 2193 | 0.0181          | 26.5709 | 18.6691 |
| 0.1097        | 130.0 | 2210 | 0.0179          | 26.5709 | 18.6691 |
| 0.1097        | 131.0 | 2227 | 0.0182          | 26.9088 | 18.7206 |
| 0.1097        | 132.0 | 2244 | 0.0180          | 26.936  | 18.7206 |
| 0.1097        | 133.0 | 2261 | 0.0173          | 26.936  | 18.7206 |
| 0.1097        | 134.0 | 2278 | 0.0176          | 26.936  | 18.7206 |
| 0.1097        | 135.0 | 2295 | 0.0167          | 26.936  | 18.7206 |
| 0.1097        | 136.0 | 2312 | 0.0181          | 26.8068 | 18.7206 |
| 0.1097        | 137.0 | 2329 | 0.0175          | 26.8738 | 18.7206 |
| 0.1097        | 138.0 | 2346 | 0.0158          | 26.8738 | 18.7206 |
| 0.1097        | 139.0 | 2363 | 0.0167          | 26.8738 | 18.7206 |
| 0.1097        | 140.0 | 2380 | 0.0166          | 26.8738 | 18.7206 |
| 0.1097        | 141.0 | 2397 | 0.0162          | 26.8738 | 18.7206 |
| 0.1097        | 142.0 | 2414 | 0.0160          | 26.8738 | 18.7206 |
| 0.1097        | 143.0 | 2431 | 0.0156          | 26.8738 | 18.7206 |
| 0.1097        | 144.0 | 2448 | 0.0160          | 26.8738 | 18.7206 |
| 0.1097        | 145.0 | 2465 | 0.0152          | 26.9135 | 18.7206 |
| 0.1097        | 146.0 | 2482 | 0.0148          | 26.9135 | 18.7206 |
| 0.1097        | 147.0 | 2499 | 0.0155          | 26.9135 | 18.7206 |
| 0.0913        | 148.0 | 2516 | 0.0149          | 26.9135 | 18.7206 |
| 0.0913        | 149.0 | 2533 | 0.0156          | 26.9135 | 18.7206 |
| 0.0913        | 150.0 | 2550 | 0.0155          | 26.9135 | 18.7206 |
| 0.0913        | 151.0 | 2567 | 0.0149          | 26.9135 | 18.7206 |
| 0.0913        | 152.0 | 2584 | 0.0142          | 26.9135 | 18.7206 |
| 0.0913        | 153.0 | 2601 | 0.0136          | 26.8738 | 18.7206 |
| 0.0913        | 154.0 | 2618 | 0.0141          | 26.8738 | 18.7206 |
| 0.0913        | 155.0 | 2635 | 0.0139          | 26.9135 | 18.7206 |
| 0.0913        | 156.0 | 2652 | 0.0136          | 26.9135 | 18.7206 |
| 0.0913        | 157.0 | 2669 | 0.0135          | 26.9135 | 18.7206 |
| 0.0913        | 158.0 | 2686 | 0.0141          | 26.9135 | 18.7206 |
| 0.0913        | 159.0 | 2703 | 0.0143          | 26.9135 | 18.7206 |
| 0.0913        | 160.0 | 2720 | 0.0134          | 26.9135 | 18.7206 |
| 0.0913        | 161.0 | 2737 | 0.0129          | 26.9135 | 18.7206 |
| 0.0913        | 162.0 | 2754 | 0.0129          | 26.9135 | 18.7206 |
| 0.0913        | 163.0 | 2771 | 0.0136          | 26.9135 | 18.7206 |
| 0.0913        | 164.0 | 2788 | 0.0131          | 26.9135 | 18.7206 |
| 0.0913        | 165.0 | 2805 | 0.0136          | 26.9135 | 18.7206 |
| 0.0913        | 166.0 | 2822 | 0.0131          | 26.9135 | 18.7206 |
| 0.0913        | 167.0 | 2839 | 0.0127          | 26.9135 | 18.7206 |
| 0.0913        | 168.0 | 2856 | 0.0128          | 26.9135 | 18.7206 |
| 0.0913        | 169.0 | 2873 | 0.0128          | 26.9533 | 18.7206 |
| 0.0913        | 170.0 | 2890 | 0.0131          | 26.9533 | 18.7206 |
| 0.0913        | 171.0 | 2907 | 0.0135          | 26.9533 | 18.7206 |
| 0.0913        | 172.0 | 2924 | 0.0132          | 26.9533 | 18.7206 |
| 0.0913        | 173.0 | 2941 | 0.0128          | 26.9533 | 18.7206 |
| 0.0913        | 174.0 | 2958 | 0.0127          | 26.9533 | 18.7206 |
| 0.0913        | 175.0 | 2975 | 0.0128          | 26.9533 | 18.7206 |
| 0.0913        | 176.0 | 2992 | 0.0127          | 26.9533 | 18.7206 |
| 0.0819        | 177.0 | 3009 | 0.0122          | 26.9533 | 18.7206 |
| 0.0819        | 178.0 | 3026 | 0.0119          | 26.9533 | 18.7206 |
| 0.0819        | 179.0 | 3043 | 0.0120          | 26.9533 | 18.7206 |
| 0.0819        | 180.0 | 3060 | 0.0123          | 26.9533 | 18.7206 |
| 0.0819        | 181.0 | 3077 | 0.0123          | 26.9533 | 18.7206 |
| 0.0819        | 182.0 | 3094 | 0.0122          | 26.9533 | 18.7206 |
| 0.0819        | 183.0 | 3111 | 0.0122          | 26.9533 | 18.7206 |
| 0.0819        | 184.0 | 3128 | 0.0121          | 26.9533 | 18.7206 |
| 0.0819        | 185.0 | 3145 | 0.0120          | 26.9533 | 18.7206 |
| 0.0819        | 186.0 | 3162 | 0.0119          | 26.9533 | 18.7206 |
| 0.0819        | 187.0 | 3179 | 0.0119          | 26.9533 | 18.7206 |
| 0.0819        | 188.0 | 3196 | 0.0120          | 26.9533 | 18.7206 |
| 0.0819        | 189.0 | 3213 | 0.0119          | 26.9533 | 18.7206 |
| 0.0819        | 190.0 | 3230 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 191.0 | 3247 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 192.0 | 3264 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 193.0 | 3281 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 194.0 | 3298 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 195.0 | 3315 | 0.0118          | 26.9533 | 18.7206 |
| 0.0819        | 196.0 | 3332 | 0.0118          | 26.9533 | 18.7206 |
| 0.0819        | 197.0 | 3349 | 0.0118          | 26.9533 | 18.7206 |
| 0.0819        | 198.0 | 3366 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 199.0 | 3383 | 0.0117          | 26.9533 | 18.7206 |
| 0.0819        | 200.0 | 3400 | 0.0117          | 26.9533 | 18.7206 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "t5-small-finetuned-text2log-finetuned-nl-to-fol-finetuned-nl-to-fol", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-text2log-finetuned-nl-to-fol-finetuned-nl-to-fol
===================================================================


This model is a fine-tuned version of anki08/t5-small-finetuned-text2log-finetuned-nl-to-fol on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0117
* Bleu: 26.9533
* Gen Len: 18.7206


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:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 200
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1