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--- |
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license: mit |
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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: m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1 |
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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: 41.8577 |
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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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# m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1 |
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This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the un_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3603 |
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- Bleu: 41.8577 |
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- Meteor: 0.4199 |
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- Gen Len: 41.9 |
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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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| 5.111 | 0.5 | 100 | 3.2467 | 29.5017 | 0.3371 | 42.425 | |
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| 2.1491 | 1.0 | 200 | 1.0018 | 33.0563 | 0.3593 | 41.205 | |
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| 0.5911 | 1.5 | 300 | 0.4159 | 34.5818 | 0.3705 | 42.0625 | |
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| 0.3546 | 2.0 | 400 | 0.3723 | 36.6179 | 0.3823 | 40.925 | |
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| 0.2487 | 2.5 | 500 | 0.3595 | 39.0331 | 0.3956 | 41.56 | |
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| 0.2365 | 3.0 | 600 | 0.3485 | 39.5188 | 0.4023 | 41.6425 | |
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| 0.1687 | 3.5 | 700 | 0.3542 | 40.1728 | 0.4043 | 42.61 | |
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| 0.1791 | 4.0 | 800 | 0.3466 | 40.4858 | 0.4101 | 41.5575 | |
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| 0.1196 | 4.5 | 900 | 0.3493 | 41.2457 | 0.4123 | 41.755 | |
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| 0.1394 | 5.0 | 1000 | 0.3486 | 40.5606 | 0.4114 | 41.78 | |
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| 0.0958 | 5.5 | 1100 | 0.3568 | 41.1873 | 0.4157 | 41.7275 | |
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| 0.1043 | 6.0 | 1200 | 0.3557 | 41.2749 | 0.4165 | 41.935 | |
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| 0.073 | 6.5 | 1300 | 0.3603 | 41.8577 | 0.4199 | 41.9 | |
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### Framework versions |
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- Transformers 4.20.1 |
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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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