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t5-small-finetuned-text2log-compute-metrics-v5-400
This model is a fine-tuned version of mrm8488/t5-small-finetuned-text2log on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5820
- Bleu: 30.1378
- Gen Len: 18.568
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: 150
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 23 | 1.5732 | 8.4784 | 17.3373 |
| No log | 2.0 | 46 | 1.1400 | 22.8492 | 18.8284 |
| No log | 3.0 | 69 | 0.9426 | 27.2247 | 18.787 |
| No log | 4.0 | 92 | 0.8110 | 26.0131 | 18.7101 |
| No log | 5.0 | 115 | 0.7559 | 24.1316 | 18.7988 |
| No log | 6.0 | 138 | 0.7102 | 25.4664 | 18.7692 |
| No log | 7.0 | 161 | 0.6807 | 26.2651 | 18.6923 |
| No log | 8.0 | 184 | 0.6575 | 27.5298 | 18.6213 |
| No log | 9.0 | 207 | 0.6369 | 28.8178 | 18.5976 |
| No log | 10.0 | 230 | 0.6250 | 27.2363 | 18.6864 |
| No log | 11.0 | 253 | 0.6143 | 28.7917 | 18.6391 |
| No log | 12.0 | 276 | 0.5973 | 29.6901 | 18.7041 |
| No log | 13.0 | 299 | 0.5864 | 29.6632 | 18.6568 |
| No log | 14.0 | 322 | 0.5827 | 29.874 | 18.6391 |
| No log | 15.0 | 345 | 0.5700 | 29.6188 | 18.6864 |
| No log | 16.0 | 368 | 0.5620 | 29.9895 | 18.7278 |
| No log | 17.0 | 391 | 0.5569 | 29.3883 | 18.7278 |
| No log | 18.0 | 414 | 0.5486 | 29.783 | 18.6864 |
| No log | 19.0 | 437 | 0.5520 | 29.4199 | 18.6568 |
| No log | 20.0 | 460 | 0.5496 | 28.8502 | 18.6923 |
| No log | 21.0 | 483 | 0.5495 | 29.2369 | 18.7337 |
| 0.8287 | 22.0 | 506 | 0.5411 | 29.1707 | 18.6923 |
| 0.8287 | 23.0 | 529 | 0.5325 | 28.8466 | 18.6923 |
| 0.8287 | 24.0 | 552 | 0.5388 | 29.2703 | 18.6746 |
| 0.8287 | 25.0 | 575 | 0.5288 | 28.7683 | 18.7278 |
| 0.8287 | 26.0 | 598 | 0.5299 | 28.3489 | 18.7337 |
| 0.8287 | 27.0 | 621 | 0.5314 | 28.2042 | 18.7278 |
| 0.8287 | 28.0 | 644 | 0.5159 | 29.5603 | 18.7574 |
| 0.8287 | 29.0 | 667 | 0.5163 | 28.8959 | 18.6982 |
| 0.8287 | 30.0 | 690 | 0.5170 | 30.0671 | 18.7219 |
| 0.8287 | 31.0 | 713 | 0.5202 | 28.9559 | 18.6686 |
| 0.8287 | 32.0 | 736 | 0.5181 | 28.1951 | 18.7574 |
| 0.8287 | 33.0 | 759 | 0.5134 | 28.2097 | 18.7041 |
| 0.8287 | 34.0 | 782 | 0.5134 | 28.0953 | 18.7574 |
| 0.8287 | 35.0 | 805 | 0.5165 | 28.4171 | 18.7988 |
| 0.8287 | 36.0 | 828 | 0.5195 | 28.7953 | 18.7633 |
| 0.8287 | 37.0 | 851 | 0.5185 | 29.1606 | 18.7633 |
| 0.8287 | 38.0 | 874 | 0.5192 | 29.5226 | 18.6805 |
| 0.8287 | 39.0 | 897 | 0.5178 | 28.425 | 18.7692 |
| 0.8287 | 40.0 | 920 | 0.5196 | 29.4795 | 18.7041 |
| 0.8287 | 41.0 | 943 | 0.5161 | 29.5127 | 18.7041 |
| 0.8287 | 42.0 | 966 | 0.5164 | 28.6225 | 18.7574 |
| 0.8287 | 43.0 | 989 | 0.5183 | 29.0629 | 18.6272 |
| 0.3866 | 44.0 | 1012 | 0.5174 | 28.6628 | 18.6213 |
| 0.3866 | 45.0 | 1035 | 0.5141 | 28.499 | 18.6213 |
| 0.3866 | 46.0 | 1058 | 0.5151 | 28.1309 | 18.6272 |
| 0.3866 | 47.0 | 1081 | 0.5167 | 29.8871 | 18.6391 |
| 0.3866 | 48.0 | 1104 | 0.5133 | 28.7513 | 18.6331 |
| 0.3866 | 49.0 | 1127 | 0.5188 | 28.3089 | 18.6213 |
| 0.3866 | 50.0 | 1150 | 0.5203 | 28.8714 | 18.6331 |
| 0.3866 | 51.0 | 1173 | 0.5263 | 28.7644 | 18.6331 |
| 0.3866 | 52.0 | 1196 | 0.5222 | 28.4817 | 18.6331 |
| 0.3866 | 53.0 | 1219 | 0.5307 | 28.8117 | 18.6272 |
| 0.3866 | 54.0 | 1242 | 0.5255 | 29.3844 | 18.6213 |
| 0.3866 | 55.0 | 1265 | 0.5264 | 29.7108 | 18.6213 |
| 0.3866 | 56.0 | 1288 | 0.5272 | 29.353 | 18.6331 |
| 0.3866 | 57.0 | 1311 | 0.5283 | 28.5792 | 18.6391 |
| 0.3866 | 58.0 | 1334 | 0.5301 | 29.9914 | 18.6272 |
| 0.3866 | 59.0 | 1357 | 0.5320 | 29.3162 | 18.6272 |
| 0.3866 | 60.0 | 1380 | 0.5380 | 29.2162 | 18.6272 |
| 0.3866 | 61.0 | 1403 | 0.5349 | 28.5292 | 18.6272 |
| 0.3866 | 62.0 | 1426 | 0.5313 | 28.7165 | 18.6627 |
| 0.3866 | 63.0 | 1449 | 0.5335 | 29.3637 | 18.6154 |
| 0.3866 | 64.0 | 1472 | 0.5350 | 29.3612 | 18.568 |
| 0.3866 | 65.0 | 1495 | 0.5330 | 29.1338 | 18.5621 |
| 0.283 | 66.0 | 1518 | 0.5322 | 29.0514 | 18.5562 |
| 0.283 | 67.0 | 1541 | 0.5362 | 29.2592 | 18.5562 |
| 0.283 | 68.0 | 1564 | 0.5379 | 29.6757 | 18.568 |
| 0.283 | 69.0 | 1587 | 0.5386 | 29.5012 | 18.5976 |
| 0.283 | 70.0 | 1610 | 0.5379 | 29.6616 | 18.5917 |
| 0.283 | 71.0 | 1633 | 0.5364 | 29.8762 | 18.6154 |
| 0.283 | 72.0 | 1656 | 0.5392 | 29.7143 | 18.6036 |
| 0.283 | 73.0 | 1679 | 0.5438 | 29.385 | 18.5976 |
| 0.283 | 74.0 | 1702 | 0.5386 | 28.3472 | 18.6095 |
| 0.283 | 75.0 | 1725 | 0.5372 | 29.1045 | 18.574 |
| 0.283 | 76.0 | 1748 | 0.5406 | 29.0839 | 18.6095 |
| 0.283 | 77.0 | 1771 | 0.5408 | 29.735 | 18.5799 |
| 0.283 | 78.0 | 1794 | 0.5406 | 29.5432 | 18.6036 |
| 0.283 | 79.0 | 1817 | 0.5413 | 29.1501 | 18.5976 |
| 0.283 | 80.0 | 1840 | 0.5434 | 29.5822 | 18.6095 |
| 0.283 | 81.0 | 1863 | 0.5491 | 29.1933 | 18.5799 |
| 0.283 | 82.0 | 1886 | 0.5473 | 28.9065 | 18.5385 |
| 0.283 | 83.0 | 1909 | 0.5507 | 29.4129 | 18.5385 |
| 0.283 | 84.0 | 1932 | 0.5534 | 29.2249 | 18.5385 |
| 0.283 | 85.0 | 1955 | 0.5561 | 29.6955 | 18.5799 |
| 0.283 | 86.0 | 1978 | 0.5575 | 29.1081 | 18.5385 |
| 0.2296 | 87.0 | 2001 | 0.5531 | 29.7633 | 18.5385 |
| 0.2296 | 88.0 | 2024 | 0.5548 | 30.045 | 18.5385 |
| 0.2296 | 89.0 | 2047 | 0.5567 | 29.9209 | 18.5385 |
| 0.2296 | 90.0 | 2070 | 0.5577 | 29.1879 | 18.5858 |
| 0.2296 | 91.0 | 2093 | 0.5602 | 29.1587 | 18.5799 |
| 0.2296 | 92.0 | 2116 | 0.5595 | 29.5205 | 18.5799 |
| 0.2296 | 93.0 | 2139 | 0.5605 | 29.3439 | 18.5325 |
| 0.2296 | 94.0 | 2162 | 0.5583 | 29.4742 | 18.5325 |
| 0.2296 | 95.0 | 2185 | 0.5576 | 29.132 | 18.5325 |
| 0.2296 | 96.0 | 2208 | 0.5566 | 29.0861 | 18.5325 |
| 0.2296 | 97.0 | 2231 | 0.5584 | 29.6618 | 18.5385 |
| 0.2296 | 98.0 | 2254 | 0.5593 | 29.1068 | 18.5325 |
| 0.2296 | 99.0 | 2277 | 0.5603 | 29.7081 | 18.5385 |
| 0.2296 | 100.0 | 2300 | 0.5599 | 29.6368 | 18.5325 |
| 0.2296 | 101.0 | 2323 | 0.5598 | 29.6263 | 18.5325 |
| 0.2296 | 102.0 | 2346 | 0.5637 | 29.6321 | 18.5385 |
| 0.2296 | 103.0 | 2369 | 0.5678 | 29.6306 | 18.5266 |
| 0.2296 | 104.0 | 2392 | 0.5685 | 29.3279 | 18.5325 |
| 0.2296 | 105.0 | 2415 | 0.5680 | 29.1363 | 18.5621 |
| 0.2296 | 106.0 | 2438 | 0.5726 | 29.2666 | 18.5385 |
| 0.2296 | 107.0 | 2461 | 0.5738 | 29.2981 | 18.5385 |
| 0.2296 | 108.0 | 2484 | 0.5740 | 29.5752 | 18.5385 |
| 0.1942 | 109.0 | 2507 | 0.5749 | 29.5596 | 18.5385 |
| 0.1942 | 110.0 | 2530 | 0.5732 | 29.6728 | 18.574 |
| 0.1942 | 111.0 | 2553 | 0.5738 | 29.6052 | 18.5325 |
| 0.1942 | 112.0 | 2576 | 0.5731 | 29.5143 | 18.574 |
| 0.1942 | 113.0 | 2599 | 0.5744 | 29.8059 | 18.574 |
| 0.1942 | 114.0 | 2622 | 0.5751 | 29.6796 | 18.574 |
| 0.1942 | 115.0 | 2645 | 0.5763 | 29.9279 | 18.568 |
| 0.1942 | 116.0 | 2668 | 0.5746 | 29.892 | 18.568 |
| 0.1942 | 117.0 | 2691 | 0.5741 | 29.8104 | 18.574 |
| 0.1942 | 118.0 | 2714 | 0.5759 | 29.6379 | 18.574 |
| 0.1942 | 119.0 | 2737 | 0.5777 | 29.7949 | 18.574 |
| 0.1942 | 120.0 | 2760 | 0.5776 | 29.6297 | 18.574 |
| 0.1942 | 121.0 | 2783 | 0.5789 | 29.5298 | 18.574 |
| 0.1942 | 122.0 | 2806 | 0.5794 | 29.6102 | 18.574 |
| 0.1942 | 123.0 | 2829 | 0.5799 | 29.7981 | 18.574 |
| 0.1942 | 124.0 | 2852 | 0.5811 | 30.0894 | 18.574 |
| 0.1942 | 125.0 | 2875 | 0.5826 | 29.9849 | 18.574 |
| 0.1942 | 126.0 | 2898 | 0.5829 | 29.8349 | 18.574 |
| 0.1942 | 127.0 | 2921 | 0.5817 | 29.6295 | 18.574 |
| 0.1942 | 128.0 | 2944 | 0.5809 | 29.5264 | 18.568 |
| 0.1942 | 129.0 | 2967 | 0.5813 | 29.5858 | 18.568 |
| 0.1942 | 130.0 | 2990 | 0.5843 | 29.6556 | 18.568 |
| 0.1777 | 131.0 | 3013 | 0.5836 | 30.0165 | 18.568 |
| 0.1777 | 132.0 | 3036 | 0.5835 | 29.8399 | 18.568 |
| 0.1777 | 133.0 | 3059 | 0.5824 | 29.8065 | 18.568 |
| 0.1777 | 134.0 | 3082 | 0.5821 | 29.8948 | 18.574 |
| 0.1777 | 135.0 | 3105 | 0.5808 | 29.9342 | 18.574 |
| 0.1777 | 136.0 | 3128 | 0.5810 | 29.7556 | 18.574 |
| 0.1777 | 137.0 | 3151 | 0.5813 | 30.0425 | 18.568 |
| 0.1777 | 138.0 | 3174 | 0.5822 | 30.0719 | 18.568 |
| 0.1777 | 139.0 | 3197 | 0.5823 | 30.0719 | 18.568 |
| 0.1777 | 140.0 | 3220 | 0.5828 | 30.1124 | 18.568 |
| 0.1777 | 141.0 | 3243 | 0.5826 | 30.1451 | 18.568 |
| 0.1777 | 142.0 | 3266 | 0.5828 | 30.1451 | 18.568 |
| 0.1777 | 143.0 | 3289 | 0.5829 | 30.1451 | 18.568 |
| 0.1777 | 144.0 | 3312 | 0.5829 | 30.1451 | 18.568 |
| 0.1777 | 145.0 | 3335 | 0.5825 | 30.1378 | 18.568 |
| 0.1777 | 146.0 | 3358 | 0.5824 | 30.1378 | 18.568 |
| 0.1777 | 147.0 | 3381 | 0.5822 | 30.1378 | 18.568 |
| 0.1777 | 148.0 | 3404 | 0.5820 | 30.1378 | 18.568 |
| 0.1777 | 149.0 | 3427 | 0.5821 | 30.1378 | 18.568 |
| 0.1777 | 150.0 | 3450 | 0.5820 | 30.1378 | 18.568 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
