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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- musabg/wikipedia-tr-summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-xl-tr-summarization |
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results: |
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- task: |
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name: Summarization |
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type: summarization |
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dataset: |
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name: musabg/wikipedia-tr-summarization |
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type: musabg/wikipedia-tr-summarization |
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split: validation |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 56.4468 |
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language: |
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- tr |
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--- |
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# mT5-Xl Turkish Summarization |
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This model is a fine-tuned version of [google/mt5-xl](https://huggingface.co/google/mt5-xl) on the musabg/wikipedia-tr-summarization dataset. |
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This can be used with HF summarization pipeline. |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 1.0 |
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### Eval results |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5676 |
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- Rouge1: 56.4468 |
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- Rouge2: 41.3258 |
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- Rougel: 48.1909 |
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- Rougelsum: 48.4284 |
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- Gen Len: 75.9265 |
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### Training results |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 1.13.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
