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--- |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- wiki_lingua |
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model-index: |
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- name: mbart-large-50-finetuned-ar-wikilingua |
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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-large-50-finetuned-ar-wikilingua |
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This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the wiki_lingua dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.0001 |
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- Rouge-1: 22.11 |
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- Rouge-2: 7.33 |
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- Rouge-l: 19.75 |
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- Gen Len: 59.4 |
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- Bertscore: 68.9 |
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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: 1e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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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- lr_scheduler_warmup_steps: 250 |
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- num_epochs: 8 |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:| |
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| 5.2671 | 1.0 | 5111 | 4.6414 | 18.37 | 5.63 | 16.32 | 96.39 | 65.12 | |
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| 4.5375 | 2.0 | 10222 | 4.3144 | 20.49 | 6.64 | 18.35 | 95.44 | 65.79 | |
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| 4.308 | 3.0 | 15333 | 4.1592 | 21.16 | 7.09 | 18.85 | 67.75 | 67.65 | |
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| 4.1562 | 4.0 | 20444 | 4.0812 | 21.59 | 7.31 | 19.42 | 68.66 | 68.02 | |
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| 4.0749 | 5.0 | 25555 | 4.0409 | 21.99 | 7.42 | 19.82 | 66.4 | 68.05 | |
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| 4.0271 | 6.0 | 30666 | 4.0183 | 22.04 | 7.42 | 19.64 | 56.88 | 68.95 | |
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| 3.9991 | 7.0 | 35777 | 4.0042 | 22.05 | 7.35 | 19.71 | 55.75 | 68.94 | |
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| 3.9833 | 8.0 | 40888 | 4.0001 | 22.12 | 7.39 | 19.78 | 55.72 | 69.0 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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