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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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datasets: |
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- un_multi |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-en-ar-finetuned-en-to-ar |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: un_multi |
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type: un_multi |
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args: ar-en |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 64.6767 |
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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-en-ar-finetuned-en-to-ar |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the un_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8133 |
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- Bleu: 64.6767 |
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- Gen Len: 17.595 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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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: 16 |
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- eval_batch_size: 16 |
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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: 16 |
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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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| No log | 1.0 | 50 | 0.7710 | 64.3416 | 17.4 | |
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| No log | 2.0 | 100 | 0.7569 | 63.9546 | 17.465 | |
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| No log | 3.0 | 150 | 0.7570 | 64.7484 | 17.385 | |
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| No log | 4.0 | 200 | 0.7579 | 65.4073 | 17.305 | |
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| No log | 5.0 | 250 | 0.7624 | 64.8939 | 17.325 | |
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| No log | 6.0 | 300 | 0.7696 | 65.1257 | 17.45 | |
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| No log | 7.0 | 350 | 0.7747 | 65.527 | 17.395 | |
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| No log | 8.0 | 400 | 0.7791 | 65.1357 | 17.52 | |
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| No log | 9.0 | 450 | 0.7900 | 65.3812 | 17.415 | |
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| 0.3982 | 10.0 | 500 | 0.7925 | 65.7346 | 17.39 | |
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| 0.3982 | 11.0 | 550 | 0.7951 | 65.1267 | 17.62 | |
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| 0.3982 | 12.0 | 600 | 0.8040 | 64.6874 | 17.495 | |
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| 0.3982 | 13.0 | 650 | 0.8069 | 64.7788 | 17.52 | |
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| 0.3982 | 14.0 | 700 | 0.8105 | 64.6701 | 17.585 | |
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| 0.3982 | 15.0 | 750 | 0.8120 | 64.7111 | 17.58 | |
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| 0.3982 | 16.0 | 800 | 0.8133 | 64.6767 | 17.595 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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