t5-small-finetuned-it-to-en
This model is a fine-tuned version of t5-small on the ccmatrix dataset. It achieves the following results on the evaluation set:
- Loss: 2.4066
- Bleu: 13.5927
- Gen Len: 28.6473
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 282 | 2.9032 | 7.2452 | 35.1327 |
| 3.2663 | 2.0 | 564 | 2.8156 | 8.3336 | 31.2673 |
| 3.2663 | 3.0 | 846 | 2.7615 | 9.1403 | 30.248 |
| 3.0467 | 4.0 | 1128 | 2.7211 | 9.2676 | 30.2893 |
| 3.0467 | 5.0 | 1410 | 2.6872 | 9.5597 | 30.4067 |
| 2.9575 | 6.0 | 1692 | 2.6600 | 9.907 | 30.3153 |
| 2.9575 | 7.0 | 1974 | 2.6361 | 10.2292 | 29.902 |
| 2.8814 | 8.0 | 2256 | 2.6132 | 10.4384 | 30.1187 |
| 2.8284 | 9.0 | 2538 | 2.5930 | 10.572 | 30.0447 |
| 2.8284 | 10.0 | 2820 | 2.5774 | 10.9557 | 29.5547 |
| 2.7827 | 11.0 | 3102 | 2.5604 | 11.1435 | 29.5847 |
| 2.7827 | 12.0 | 3384 | 2.5484 | 11.4067 | 29.4807 |
| 2.7496 | 13.0 | 3666 | 2.5342 | 11.569 | 29.5827 |
| 2.7496 | 14.0 | 3948 | 2.5208 | 11.7581 | 30.07 |
| 2.7094 | 15.0 | 4230 | 2.5105 | 11.9629 | 29.6993 |
| 2.6764 | 16.0 | 4512 | 2.5007 | 12.2675 | 29.1 |
| 2.6764 | 17.0 | 4794 | 2.4916 | 12.2227 | 29.4 |
| 2.6516 | 18.0 | 5076 | 2.4817 | 12.3529 | 29.222 |
| 2.6516 | 19.0 | 5358 | 2.4747 | 12.6053 | 29.036 |
| 2.6271 | 20.0 | 5640 | 2.4672 | 12.6659 | 29.0993 |
| 2.6271 | 21.0 | 5922 | 2.4602 | 12.8286 | 29.2087 |
| 2.602 | 22.0 | 6204 | 2.4546 | 12.8915 | 29.0233 |
| 2.602 | 23.0 | 6486 | 2.4486 | 12.7892 | 29.2173 |
| 2.5922 | 24.0 | 6768 | 2.4438 | 12.8928 | 29.042 |
| 2.5781 | 25.0 | 7050 | 2.4386 | 13.1954 | 28.8607 |
| 2.5781 | 26.0 | 7332 | 2.4341 | 13.0077 | 28.8367 |
| 2.5578 | 27.0 | 7614 | 2.4306 | 13.1084 | 28.7487 |
| 2.5578 | 28.0 | 7896 | 2.4258 | 13.0929 | 28.9067 |
| 2.5477 | 29.0 | 8178 | 2.4236 | 13.2008 | 28.966 |
| 2.5477 | 30.0 | 8460 | 2.4203 | 13.3476 | 28.7133 |
| 2.5331 | 31.0 | 8742 | 2.4170 | 13.3539 | 28.8787 |
| 2.5312 | 32.0 | 9024 | 2.4148 | 13.3781 | 28.742 |
| 2.5312 | 33.0 | 9306 | 2.4130 | 13.3425 | 28.8393 |
| 2.5234 | 34.0 | 9588 | 2.4113 | 13.4549 | 28.732 |
| 2.5234 | 35.0 | 9870 | 2.4099 | 13.5228 | 28.8313 |
| 2.5131 | 36.0 | 10152 | 2.4084 | 13.547 | 28.6733 |
| 2.5131 | 37.0 | 10434 | 2.4076 | 13.6099 | 28.5193 |
| 2.5101 | 38.0 | 10716 | 2.4071 | 13.5853 | 28.64 |
| 2.5101 | 39.0 | 10998 | 2.4067 | 13.572 | 28.6687 |
| 2.5136 | 40.0 | 11280 | 2.4066 | 13.5927 | 28.6473 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1
- Datasets 2.5.1
- Tokenizers 0.11.0