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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/mbart-large-50 |
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tags: |
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- simplification |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: mbart-translation-DDHH |
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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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# mbart-translation-DDHH |
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This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) trained on a parallel English–Spanish corpus of the Universal Declaration of Human Rights. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6758 |
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- Bleu: 33.4177 |
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- Gen Len: 25.95 |
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## Model description |
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This model is based on mBART-50, a multilingual sequence-to-sequence model, and has been fine-tuned to improve the quality of translations between English and Spanish for the specific domain of legal/human-rights text. It is designed to produce fluent and accurate sentence-level translations that maintain the formal tone and legal register of the source material. |
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## Intended uses & limitations |
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Intended use: Automatic English↔Spanish translation of legal or policy-oriented texts, especially those similar in style to the Universal Declaration of Human Rights. |
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Limitations: specialized in one specific domain (the Universal Declaration of Human Rights) and may not generalize well to informal or highly technical text outside this domain. |
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## Training and evaluation data |
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The model was fine-tuned on a parallel corpus of the Universal Declaration of Human Rights in English and Spanish. The training set included sentence-aligned text segments extracted from publicly available translations of the declaration. |
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## Training procedure |
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The fine-tuning was conducted on a single GPU using the transformers library from Hugging Face. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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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 | 10 | 3.8374 | 28.2511 | 23.65 | |
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| No log | 2.0 | 20 | 3.6758 | 33.4177 | 25.95 | |
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### Framework versions |
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- Transformers 4.52.4 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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