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README.md
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---
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base_model: facebook/mbart-large-50-many-to-many-mmt
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tags:
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- translation
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- mBART
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metrics:
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- bleu
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model-index:
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- name: mbart-en-np-seqtoseq-sentence-translation
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/darvilab/Training%20Sentence%20Translation/runs/nul533k2)
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# mbart-en-np-seqtoseq-sentence-translation
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This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1896
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- Bleu: 40.4595
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- Gen Len: 10.288
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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: 5
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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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| 1.0147 | 1.0 | 1250 | 0.9876 | 40.1501 | 9.885 |
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| 0.6038 | 2.0 | 2500 | 1.0122 | 40.728 | 10.113 |
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| 0.3557 | 3.0 | 3750 | 1.0809 | 35.9297 | 10.844 |
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| 0.2071 | 4.0 | 5000 | 1.1502 | 40.4318 | 10.28 |
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| 0.1241 | 5.0 | 6250 | 1.1896 | 40.4595 | 10.288 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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