medical_en_zh_8_29
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-zh on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6159
- Bleu: 41.4839
- Gen Len: 77.4048
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: 0.0004
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
---|---|---|---|---|---|
1.5915 | 1.02 | 3000 | 1.4640 | 30.8193 | 76.572 |
1.2908 | 2.04 | 6000 | 1.2734 | 32.3053 | 76.897 |
1.0814 | 3.06 | 9000 | 1.1348 | 34.3605 | 77.2082 |
0.9083 | 4.08 | 12000 | 1.0246 | 34.9139 | 76.7213 |
0.7507 | 5.1 | 15000 | 0.9336 | 36.2245 | 76.6036 |
0.6046 | 6.12 | 18000 | 0.8291 | 37.987 | 77.326 |
0.4838 | 7.14 | 21000 | 0.7496 | 38.7572 | 77.2366 |
0.3861 | 8.16 | 24000 | 0.6730 | 40.3566 | 77.49 |
0.3203 | 9.19 | 27000 | 0.6159 | 41.4839 | 77.4048 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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Base model
Helsinki-NLP/opus-mt-en-zh