t5-small-finetuned-v2-chinese-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: 1.7757
- Bleu: 1.9523
- Gen Len: 18.6997
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: 0.0006
- 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: 3000
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 3.5237 | 1.0 | 1103 | 2.5564 | 0.9857 | 18.8055 |
| 2.5377 | 2.0 | 2206 | 2.1815 | 1.6392 | 18.7259 |
| 2.2418 | 3.0 | 3309 | 2.0216 | 1.8732 | 18.5659 |
| 2.0818 | 4.0 | 4412 | 1.9331 | 1.9183 | 18.1569 |
| 1.9874 | 5.0 | 5515 | 1.8834 | 1.6409 | 18.0559 |
| 1.9213 | 6.0 | 6618 | 1.8511 | 1.9679 | 18.6534 |
| 1.8712 | 7.0 | 7721 | 1.8295 | 1.8632 | 18.4841 |
| 1.8292 | 8.0 | 8824 | 1.8101 | 2.5462 | 18.5024 |
| 1.7949 | 9.0 | 9927 | 1.7990 | 1.847 | 18.3106 |
| 1.7666 | 10.0 | 11030 | 1.7867 | 1.849 | 18.4893 |
| 1.7428 | 11.0 | 12133 | 1.7826 | 1.7849 | 18.6368 |
| 1.7256 | 12.0 | 13236 | 1.7757 | 1.9587 | 18.7077 |
| 1.7124 | 13.0 | 14339 | 1.7746 | 2.2943 | 18.5367 |
| 1.7051 | 14.0 | 15442 | 1.7757 | 1.9676 | 18.7081 |
| 1.7001 | 15.0 | 16545 | 1.7757 | 1.9523 | 18.6997 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1