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mbart-finetune-ar-xlsum
eslamxm/mbart-finetune-ar-xlsum
mbart-finetune-ar-xlsum is a summarization model from eslamxm. Use it when you need a shorter version of a longer text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Summarization
- Library
- transformers
- Model type
- mbart
- Access
- Public
- Created
- Jun 18, 2022
- Updated
- Jun 19, 2022
- SHA
- 64bb51fb
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
mbart-finetune-ar-xlsum
This model is a fine-tuned version of facebook/mbart-large-50 on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 4.4328
- Rouge-1: 15.56
- Rouge-2: 4.64
- Rouge-l: 13.59
- Gen Len: 38.86
- Bertscore: 71.53
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 5
- label_smoothing_factor: 0.1
Training results
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Summarization
- Library
- transformers
- Type
- mbart
- Created
- Jun 18, 2022
- Updated
- Jun 19, 2022