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update model card README.md
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README.md
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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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- opus100
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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-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3
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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: opus100
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type: opus100
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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: 27.5576
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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-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3
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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 opus100 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2352
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- Bleu: 27.5576
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- Meteor: 0.1675
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- Gen Len: 11.4225
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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: 8
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- eval_batch_size: 8
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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: 11
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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 | Meteor | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
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| 1.0592 | 0.5 | 100 | 0.2330 | 27.1301 | 0.1711 | 11.6275 |
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| 0.1805 | 1.0 | 200 | 0.2286 | 28.7262 | 0.1732 | 11.355 |
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| 0.1454 | 1.5 | 300 | 0.2283 | 28.0642 | 0.1754 | 11.4775 |
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| 0.1457 | 2.0 | 400 | 0.2292 | 27.5737 | 0.1716 | 11.535 |
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| 0.1153 | 2.5 | 500 | 0.2298 | 25.3882 | 0.1729 | 12.3825 |
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| 0.1267 | 3.0 | 600 | 0.2321 | 27.8985 | 0.1689 | 11.7675 |
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| 0.1045 | 3.5 | 700 | 0.2336 | 26.6215 | 0.1661 | 12.0825 |
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| 0.101 | 4.0 | 800 | 0.2352 | 27.5576 | 0.1675 | 11.4225 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.11.0
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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