t5-small-finetuned-hausa-to-chinese
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: 0.3817
- Bleu: 30.2633
- Gen Len: 3.5559
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 4000
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.6981 | 1.0 | 846 | 0.2900 | 14.2476 | 3.4917 |
| 0.3149 | 2.0 | 1692 | 0.2639 | 18.6104 | 3.4725 |
| 0.2782 | 3.0 | 2538 | 0.2467 | 9.1092 | 3.2542 |
| 0.2622 | 4.0 | 3384 | 0.2481 | 24.1345 | 3.4047 |
| 0.2428 | 5.0 | 4230 | 0.2529 | 16.9217 | 3.3965 |
| 0.2271 | 6.0 | 5076 | 0.2491 | 27.8491 | 3.5349 |
| 0.2047 | 7.0 | 5922 | 0.2507 | 16.6565 | 3.339 |
| 0.1902 | 8.0 | 6768 | 0.2506 | 25.6462 | 3.5667 |
| 0.1739 | 9.0 | 7614 | 0.2610 | 27.1673 | 3.5916 |
| 0.1587 | 10.0 | 8460 | 0.2438 | 29.306 | 3.5839 |
| 0.1425 | 11.0 | 9306 | 0.2660 | 29.08 | 3.6478 |
| 0.1251 | 12.0 | 10152 | 0.2721 | 29.9148 | 3.4994 |
| 0.1105 | 13.0 | 10998 | 0.2929 | 28.1895 | 3.5526 |
| 0.0956 | 14.0 | 11844 | 0.3010 | 30.552 | 3.5717 |
| 0.083 | 15.0 | 12690 | 0.3307 | 27.9728 | 3.5303 |
| 0.0724 | 16.0 | 13536 | 0.3404 | 27.1874 | 3.5146 |
| 0.0652 | 17.0 | 14382 | 0.3592 | 29.9567 | 3.5529 |
| 0.0568 | 18.0 | 15228 | 0.3774 | 30.5145 | 3.5668 |
| 0.0549 | 19.0 | 16074 | 0.3795 | 30.6604 | 3.5637 |
| 0.0526 | 20.0 | 16920 | 0.3817 | 30.2633 | 3.5559 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1