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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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- opus100 |
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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-2000instancesopus-leaningRate2e-05-batchSize16-20epoch-1 |
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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: 13.1835 |
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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-2000instancesopus-leaningRate2e-05-batchSize16-20epoch-1 |
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This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the opus100 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3640 |
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- Bleu: 13.1835 |
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- Meteor: 0.1189 |
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- Gen Len: 17.72 |
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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: 20 |
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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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| 6.1776 | 1.0 | 100 | 3.8904 | 10.5866 | 0.0995 | 16.64 | |
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| 2.4531 | 2.0 | 200 | 1.0928 | 12.3452 | 0.1108 | 17.0575 | |
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| 0.512 | 3.0 | 300 | 0.3625 | 10.5224 | 0.0982 | 17.2575 | |
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| 0.1924 | 4.0 | 400 | 0.3342 | 12.4242 | 0.1098 | 16.6325 | |
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| 0.1227 | 5.0 | 500 | 0.3403 | 13.0526 | 0.1185 | 17.3475 | |
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| 0.0889 | 6.0 | 600 | 0.3481 | 13.1323 | 0.1133 | 17.815 | |
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| 0.0651 | 7.0 | 700 | 0.3601 | 12.6684 | 0.1133 | 17.3525 | |
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| 0.0533 | 8.0 | 800 | 0.3640 | 13.1835 | 0.1189 | 17.72 | |
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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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