t5-small-finetuned-v2-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: 1.1509
- Bleu: 30.0183
- Gen Len: 6.4896
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 |
---|---|---|---|---|---|
1.643 | 1.0 | 1103 | 1.1585 | 24.9091 | 6.7771 |
1.1913 | 2.0 | 2206 | 1.0817 | 24.5257 | 6.7541 |
1.0945 | 3.0 | 3309 | 1.0737 | 27.3158 | 6.4568 |
1.0113 | 4.0 | 4412 | 1.0400 | 27.6138 | 6.6673 |
0.9415 | 5.0 | 5515 | 1.0556 | 26.3585 | 6.335 |
0.8809 | 6.0 | 6618 | 1.0479 | 25.5111 | 6.4373 |
0.8281 | 7.0 | 7721 | 1.0496 | 26.9639 | 6.2402 |
0.7805 | 8.0 | 8824 | 1.0687 | 28.3541 | 6.4397 |
0.7351 | 9.0 | 9927 | 1.0859 | 28.7719 | 6.4876 |
0.6941 | 10.0 | 11030 | 1.1064 | 27.9477 | 6.2022 |
0.6621 | 11.0 | 12133 | 1.1114 | 29.7176 | 6.4492 |
0.6361 | 12.0 | 13236 | 1.1379 | 29.5086 | 6.4459 |
0.6165 | 13.0 | 14339 | 1.1407 | 29.7825 | 6.5262 |
0.6039 | 14.0 | 15442 | 1.1498 | 30.0064 | 6.4859 |
0.6002 | 15.0 | 16545 | 1.1509 | 30.0183 | 6.4896 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
google-t5/t5-small