t5-small-finetuned-english-to-hausa
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7088
- Bleu: 71.7187
- Gen Len: 14.3652
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: 0.0008
- 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: cosine
- lr_scheduler_warmup_steps: 3000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 3.1612 | 1.0 | 749 | 1.7523 | 32.7424 | 15.2302 |
| 1.5573 | 2.0 | 1498 | 1.0553 | 53.4401 | 14.5568 |
| 1.0462 | 3.0 | 2247 | 0.7899 | 60.8893 | 14.71 |
| 0.8071 | 4.0 | 2996 | 0.6780 | 64.3438 | 14.4066 |
| 0.6602 | 5.0 | 3745 | 0.6089 | 66.0887 | 14.127 |
| 0.5562 | 6.0 | 4494 | 0.5741 | 66.8902 | 14.1295 |
| 0.4872 | 7.0 | 5243 | 0.5497 | 68.4261 | 14.3395 |
| 0.4299 | 8.0 | 5992 | 0.5412 | 68.9385 | 14.3446 |
| 0.3872 | 9.0 | 6741 | 0.5377 | 69.5675 | 14.2603 |
| 0.3478 | 10.0 | 7490 | 0.5356 | 70.0045 | 14.3615 |
| 0.3147 | 11.0 | 8239 | 0.5312 | 70.1895 | 14.4524 |
| 0.2848 | 12.0 | 8988 | 0.5484 | 70.8151 | 14.366 |
| 0.2584 | 13.0 | 9737 | 0.5523 | 70.6127 | 14.2939 |
| 0.2342 | 14.0 | 10486 | 0.5642 | 70.7368 | 14.3301 |
| 0.2122 | 15.0 | 11235 | 0.5775 | 70.9399 | 14.3635 |
| 0.1928 | 16.0 | 11984 | 0.5935 | 71.2577 | 14.352 |
| 0.1757 | 17.0 | 12733 | 0.5964 | 71.2056 | 14.3929 |
| 0.1608 | 18.0 | 13482 | 0.6085 | 71.0265 | 14.3877 |
| 0.1475 | 19.0 | 14231 | 0.6219 | 71.5491 | 14.3812 |
| 0.1352 | 20.0 | 14980 | 0.6285 | 71.5971 | 14.3675 |
| 0.1237 | 21.0 | 15729 | 0.6468 | 71.4863 | 14.3782 |
| 0.1142 | 22.0 | 16478 | 0.6652 | 71.5849 | 14.3734 |
| 0.1082 | 23.0 | 17227 | 0.6733 | 71.6037 | 14.3298 |
| 0.0998 | 24.0 | 17976 | 0.6852 | 71.6926 | 14.4066 |
| 0.0962 | 25.0 | 18725 | 0.6899 | 71.7003 | 14.358 |
| 0.0915 | 26.0 | 19474 | 0.6994 | 71.6191 | 14.3702 |
| 0.0882 | 27.0 | 20223 | 0.7033 | 71.5731 | 14.3537 |
| 0.0857 | 28.0 | 20972 | 0.7084 | 71.6407 | 14.3618 |
| 0.0853 | 29.0 | 21721 | 0.7086 | 71.7115 | 14.3635 |
| 0.0847 | 30.0 | 22470 | 0.7088 | 71.7187 | 14.3652 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1