metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: genz_model2
results: []
genz_model2
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1282
- Bleu: 40.1672
- Gen Len: 15.25
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 | 1.9410 | 28.2848 | 15.4509 |
| No log | 2.0 | 214 | 1.7415 | 32.3881 | 15.3645 |
| No log | 3.0 | 321 | 1.6506 | 32.8796 | 15.5374 |
| No log | 4.0 | 428 | 1.5856 | 33.1982 | 15.5748 |
| 1.9676 | 5.0 | 535 | 1.5352 | 34.3335 | 15.4556 |
| 1.9676 | 6.0 | 642 | 1.4929 | 34.962 | 15.5187 |
| 1.9676 | 7.0 | 749 | 1.4595 | 35.459 | 15.535 |
| 1.9676 | 8.0 | 856 | 1.4316 | 35.6253 | 15.5421 |
| 1.9676 | 9.0 | 963 | 1.4066 | 35.9011 | 15.4953 |
| 1.5695 | 10.0 | 1070 | 1.3838 | 36.5102 | 15.4907 |
| 1.5695 | 11.0 | 1177 | 1.3608 | 36.2464 | 15.5631 |
| 1.5695 | 12.0 | 1284 | 1.3410 | 36.3368 | 15.5748 |
| 1.5695 | 13.0 | 1391 | 1.3238 | 37.2607 | 15.493 |
| 1.5695 | 14.0 | 1498 | 1.3092 | 36.9306 | 15.5234 |
| 1.4322 | 15.0 | 1605 | 1.2943 | 37.2516 | 15.5701 |
| 1.4322 | 16.0 | 1712 | 1.2812 | 37.9106 | 15.4696 |
| 1.4322 | 17.0 | 1819 | 1.2694 | 38.0468 | 15.4907 |
| 1.4322 | 18.0 | 1926 | 1.2559 | 38.0982 | 15.4836 |
| 1.3384 | 19.0 | 2033 | 1.2455 | 38.5418 | 15.4556 |
| 1.3384 | 20.0 | 2140 | 1.2375 | 38.2567 | 15.4463 |
| 1.3384 | 21.0 | 2247 | 1.2285 | 38.3496 | 15.3972 |
| 1.3384 | 22.0 | 2354 | 1.2182 | 38.6696 | 15.4393 |
| 1.3384 | 23.0 | 2461 | 1.2092 | 38.6524 | 15.4182 |
| 1.2646 | 24.0 | 2568 | 1.2013 | 38.5694 | 15.4346 |
| 1.2646 | 25.0 | 2675 | 1.1947 | 38.8347 | 15.4065 |
| 1.2646 | 26.0 | 2782 | 1.1893 | 38.7466 | 15.3738 |
| 1.2646 | 27.0 | 2889 | 1.1840 | 38.8294 | 15.3855 |
| 1.2646 | 28.0 | 2996 | 1.1795 | 38.8043 | 15.3738 |
| 1.2144 | 29.0 | 3103 | 1.1722 | 38.9285 | 15.3995 |
| 1.2144 | 30.0 | 3210 | 1.1691 | 39.1174 | 15.3435 |
| 1.2144 | 31.0 | 3317 | 1.1646 | 39.2841 | 15.3341 |
| 1.2144 | 32.0 | 3424 | 1.1612 | 39.1613 | 15.2687 |
| 1.1741 | 33.0 | 3531 | 1.1581 | 39.2741 | 15.2921 |
| 1.1741 | 34.0 | 3638 | 1.1528 | 39.3863 | 15.3014 |
| 1.1741 | 35.0 | 3745 | 1.1501 | 39.5385 | 15.264 |
| 1.1741 | 36.0 | 3852 | 1.1465 | 39.7548 | 15.2897 |
| 1.1741 | 37.0 | 3959 | 1.1448 | 39.8433 | 15.25 |
| 1.1518 | 38.0 | 4066 | 1.1415 | 39.8777 | 15.2243 |
| 1.1518 | 39.0 | 4173 | 1.1398 | 40.0676 | 15.2453 |
| 1.1518 | 40.0 | 4280 | 1.1384 | 40.0178 | 15.2033 |
| 1.1518 | 41.0 | 4387 | 1.1348 | 39.8617 | 15.278 |
| 1.1518 | 42.0 | 4494 | 1.1336 | 39.9387 | 15.2664 |
| 1.1216 | 43.0 | 4601 | 1.1322 | 40.1468 | 15.257 |
| 1.1216 | 44.0 | 4708 | 1.1314 | 40.0534 | 15.257 |
| 1.1216 | 45.0 | 4815 | 1.1305 | 40.1604 | 15.257 |
| 1.1216 | 46.0 | 4922 | 1.1297 | 40.1344 | 15.2523 |
| 1.112 | 47.0 | 5029 | 1.1290 | 40.1921 | 15.2617 |
| 1.112 | 48.0 | 5136 | 1.1285 | 40.2545 | 15.25 |
| 1.112 | 49.0 | 5243 | 1.1283 | 40.1672 | 15.25 |
| 1.112 | 50.0 | 5350 | 1.1282 | 40.1672 | 15.25 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3