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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-zh-de-tuned-Tatoeba-small |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# opus-mt-zh-de-tuned-Tatoeba-small |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-zh-de](https://huggingface.co/Helsinki-NLP/opus-mt-zh-de) on a refined dataset of Tatoeba German - Chinese corpus https://github.com/Helsinki-NLP/Tatoeba-Challenge/blob/master/data/README.md. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2703 |
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- Bleu: 16.504 |
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- Gen Len: 16.6531 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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Prefix used during fine-tuning: "将中文翻译成德语". This prefix is also recommended in prediction. |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:| |
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| 2.7229 | 0.24 | 16000 | 2.5605 | 14.1956 | 16.2206 | |
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| 2.5988 | 0.49 | 32000 | 2.4447 | 14.8619 | 16.2726 | |
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| 2.515 | 0.73 | 48000 | 2.3817 | 15.3212 | 16.2823 | |
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| 2.4683 | 0.97 | 64000 | 2.3367 | 15.9043 | 16.7138 | |
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| 2.3873 | 1.22 | 80000 | 2.3115 | 16.1037 | 16.6369 | |
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| 2.3792 | 1.46 | 96000 | 2.2919 | 16.2957 | 16.6304 | |
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| 2.3626 | 1.7 | 112000 | 2.2790 | 16.2995 | 16.6235 | |
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| 2.3353 | 1.95 | 128000 | 2.2703 | 16.504 | 16.6531 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.17.0 |
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- Tokenizers 0.10.3 |
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