t5-small-finetuned-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: 1.6584
- Bleu: 12.1339
- Gen Len: 17.7108
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: 5000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 3.7025 | 1.0 | 846 | 2.6105 | 10.8813 | 18.9939 |
| 2.5979 | 2.0 | 1692 | 2.1871 | 11.8977 | 18.9845 |
| 2.2642 | 3.0 | 2538 | 1.9964 | 10.0898 | 18.9515 |
| 2.0674 | 4.0 | 3384 | 1.8804 | 10.6493 | 17.1889 |
| 1.943 | 5.0 | 4230 | 1.8018 | 10.3424 | 18.9035 |
| 1.8501 | 6.0 | 5076 | 1.7529 | 12.523 | 18.8649 |
| 1.7736 | 7.0 | 5922 | 1.7176 | 11.9247 | 18.8803 |
| 1.711 | 8.0 | 6768 | 1.6823 | 11.623 | 18.3937 |
| 1.6537 | 9.0 | 7614 | 1.6550 | 12.3403 | 18.8995 |
| 1.6083 | 10.0 | 8460 | 1.6398 | 11.774 | 18.6873 |
| 1.5689 | 11.0 | 9306 | 1.6300 | 12.8081 | 18.8652 |
| 1.5314 | 12.0 | 10152 | 1.6279 | 12.2929 | 18.854 |
| 1.4962 | 13.0 | 10998 | 1.6197 | 12.1522 | 17.8497 |
| 1.4655 | 14.0 | 11844 | 1.6050 | 12.0764 | 17.9718 |
| 1.435 | 15.0 | 12690 | 1.6076 | 12.2447 | 17.9524 |
| 1.4047 | 16.0 | 13536 | 1.6048 | 11.4017 | 18.6209 |
| 1.38 | 17.0 | 14382 | 1.6134 | 11.5516 | 18.7405 |
| 1.3513 | 18.0 | 15228 | 1.6105 | 8.6492 | 14.2507 |
| 1.3282 | 19.0 | 16074 | 1.6174 | 12.094 | 17.7717 |
| 1.3052 | 20.0 | 16920 | 1.6239 | 11.5085 | 18.7053 |
| 1.2835 | 21.0 | 17766 | 1.6238 | 12.1588 | 17.7876 |
| 1.2653 | 22.0 | 18612 | 1.6339 | 12.0899 | 17.7112 |
| 1.2503 | 23.0 | 19458 | 1.6399 | 12.1466 | 17.7452 |
| 1.2357 | 24.0 | 20304 | 1.6461 | 9.0097 | 14.3578 |
| 1.2236 | 25.0 | 21150 | 1.6501 | 12.2617 | 17.7143 |
| 1.2139 | 26.0 | 21996 | 1.6528 | 12.1118 | 17.7233 |
| 1.2066 | 27.0 | 22842 | 1.6576 | 12.1435 | 17.7094 |
| 1.2037 | 28.0 | 23688 | 1.6568 | 12.1328 | 17.7133 |
| 1.2 | 29.0 | 24534 | 1.6581 | 12.1289 | 17.7109 |
| 1.1967 | 30.0 | 25380 | 1.6584 | 12.1339 | 17.7108 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1