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--- |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-en-fr |
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tags: |
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- waquas/lab1_random |
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- generated_from_trainer |
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datasets: |
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- kde4 |
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metrics: |
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- bleu |
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model-index: |
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- name: lab1_random |
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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: kde4 |
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type: kde4 |
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config: en-fr |
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split: train |
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args: en-fr |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 7.9976507307051765 |
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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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# lab1_random |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-fr](https://huggingface.co/Helsinki-NLP/opus-mt-en-fr) on the kde4 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.2167 |
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- Bleu: 7.9977 |
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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: 64 |
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- eval_batch_size: 128 |
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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: 1 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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