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update model card README.md
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README.md
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---
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tags:
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- summarization
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- mT5_multilingual_XLSum
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- mt5
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- abstractive summarization
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- ar
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- xlsum
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- generated_from_trainer
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datasets:
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- xlsum
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model-index:
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- name: mT5_multilingual_XLSum-finetune-ar-xlsum
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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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# mT5_multilingual_XLSum-finetune-ar-xlsum
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This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on the xlsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.2497
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- Rouge-1: 32.52
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- Rouge-2: 14.71
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- Rouge-l: 27.88
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- Gen Len: 41.45
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- Bertscore: 74.65
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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: 0.0005
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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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- gradient_accumulation_steps: 16
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- total_train_batch_size: 64
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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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| 3.5465 | 1.0 | 585 | 3.3215 | 30.09 | 13.23 | 26.07 | 36.31 | 73.97 |
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| 3.3564 | 2.0 | 1170 | 3.2547 | 31.29 | 13.93 | 26.75 | 41.68 | 74.22 |
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| 3.2185 | 3.0 | 1755 | 3.2421 | 31.78 | 14.1 | 27.07 | 41.64 | 74.4 |
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| 3.1145 | 4.0 | 2340 | 3.2241 | 31.98 | 14.38 | 27.51 | 40.29 | 74.46 |
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| 3.031 | 5.0 | 2925 | 3.2313 | 32.3 | 14.67 | 27.83 | 39.81 | 74.61 |
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| 2.9627 | 6.0 | 3510 | 3.2348 | 32.39 | 14.65 | 27.76 | 40.02 | 74.6 |
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| 2.9088 | 7.0 | 4095 | 3.2439 | 32.5 | 14.66 | 27.81 | 41.2 | 74.65 |
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| 2.8649 | 8.0 | 4680 | 3.2497 | 32.52 | 14.71 | 27.88 | 41.45 | 74.65 |
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### Framework versions
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- Transformers 4.19.4
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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