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genz_model1
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1491
- Bleu: 40.8929
- Gen Len: 14.9556
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 107 | 1.7641 | 33.597 | 15.1495 |
| No log | 2.0 | 214 | 1.6673 | 34.361 | 15.3435 |
| No log | 3.0 | 321 | 1.6087 | 34.5695 | 15.4369 |
| No log | 4.0 | 428 | 1.5600 | 35.2399 | 15.3528 |
| 1.8047 | 5.0 | 535 | 1.5171 | 35.6103 | 15.4743 |
| 1.8047 | 6.0 | 642 | 1.4851 | 36.0011 | 15.4369 |
| 1.8047 | 7.0 | 749 | 1.4512 | 35.9925 | 15.5234 |
| 1.8047 | 8.0 | 856 | 1.4261 | 36.2647 | 15.5117 |
| 1.8047 | 9.0 | 963 | 1.3992 | 36.0587 | 15.6005 |
| 1.5488 | 10.0 | 1070 | 1.3831 | 36.1956 | 15.4836 |
| 1.5488 | 11.0 | 1177 | 1.3626 | 36.409 | 15.4743 |
| 1.5488 | 12.0 | 1284 | 1.3432 | 36.6838 | 15.486 |
| 1.5488 | 13.0 | 1391 | 1.3293 | 36.4639 | 15.4696 |
| 1.5488 | 14.0 | 1498 | 1.3148 | 36.7266 | 15.4416 |
| 1.4212 | 15.0 | 1605 | 1.3005 | 36.8887 | 15.4556 |
| 1.4212 | 16.0 | 1712 | 1.2903 | 37.1891 | 15.3902 |
| 1.4212 | 17.0 | 1819 | 1.2763 | 37.6121 | 15.3972 |
| 1.4212 | 18.0 | 1926 | 1.2620 | 37.5425 | 15.4743 |
| 1.3223 | 19.0 | 2033 | 1.2561 | 37.9319 | 15.3341 |
| 1.3223 | 20.0 | 2140 | 1.2492 | 38.1299 | 15.2874 |
| 1.3223 | 21.0 | 2247 | 1.2381 | 38.364 | 15.3061 |
| 1.3223 | 22.0 | 2354 | 1.2314 | 38.9094 | 15.2523 |
| 1.3223 | 23.0 | 2461 | 1.2265 | 38.5676 | 15.2383 |
| 1.2631 | 24.0 | 2568 | 1.2159 | 39.0735 | 15.25 |
| 1.2631 | 25.0 | 2675 | 1.2125 | 38.7736 | 15.2383 |
| 1.2631 | 26.0 | 2782 | 1.2052 | 39.4841 | 15.1308 |
| 1.2631 | 27.0 | 2889 | 1.1987 | 39.3427 | 15.1612 |
| 1.2631 | 28.0 | 2996 | 1.1952 | 39.5887 | 15.1285 |
| 1.2042 | 29.0 | 3103 | 1.1932 | 39.4991 | 15.1192 |
| 1.2042 | 30.0 | 3210 | 1.1867 | 40.1521 | 15.1005 |
| 1.2042 | 31.0 | 3317 | 1.1812 | 40.3359 | 15.1285 |
| 1.2042 | 32.0 | 3424 | 1.1777 | 40.2795 | 15.0748 |
| 1.1701 | 33.0 | 3531 | 1.1748 | 40.3198 | 15.0561 |
| 1.1701 | 34.0 | 3638 | 1.1711 | 40.2025 | 15.0397 |
| 1.1701 | 35.0 | 3745 | 1.1693 | 40.4234 | 15.0514 |
| 1.1701 | 36.0 | 3852 | 1.1678 | 40.5943 | 14.9977 |
| 1.1701 | 37.0 | 3959 | 1.1645 | 40.6919 | 15.0023 |
| 1.1371 | 38.0 | 4066 | 1.1612 | 40.6628 | 14.9743 |
| 1.1371 | 39.0 | 4173 | 1.1592 | 40.6584 | 14.965 |
| 1.1371 | 40.0 | 4280 | 1.1581 | 40.5589 | 14.9626 |
| 1.1371 | 41.0 | 4387 | 1.1555 | 40.6157 | 14.9907 |
| 1.1371 | 42.0 | 4494 | 1.1546 | 40.868 | 14.9743 |
| 1.1203 | 43.0 | 4601 | 1.1527 | 40.6054 | 14.9977 |
| 1.1203 | 44.0 | 4708 | 1.1518 | 40.7963 | 14.9883 |
| 1.1203 | 45.0 | 4815 | 1.1509 | 40.7776 | 14.9766 |
| 1.1203 | 46.0 | 4922 | 1.1502 | 40.7738 | 14.9556 |
| 1.1103 | 47.0 | 5029 | 1.1499 | 40.8814 | 14.9579 |
| 1.1103 | 48.0 | 5136 | 1.1495 | 40.9137 | 14.9533 |
| 1.1103 | 49.0 | 5243 | 1.1493 | 40.8929 | 14.9556 |
| 1.1103 | 50.0 | 5350 | 1.1491 | 40.8929 | 14.9556 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
