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license: apache-2.0 |
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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-base-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-base-finetune-ar-xlsum |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.2546 |
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- Rouge-1: 22.2 |
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- Rouge-2: 9.57 |
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- Rouge-l: 20.26 |
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- Gen Len: 19.0 |
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- Bertscore: 71.43 |
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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: 10 |
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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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| 4.9261 | 1.0 | 585 | 3.6314 | 18.19 | 6.49 | 16.37 | 19.0 | 70.17 | |
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| 3.8429 | 2.0 | 1170 | 3.4253 | 19.45 | 7.58 | 17.73 | 19.0 | 70.35 | |
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| 3.6311 | 3.0 | 1755 | 3.3569 | 20.83 | 8.54 | 18.9 | 19.0 | 70.89 | |
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| 3.4917 | 4.0 | 2340 | 3.3101 | 20.77 | 8.53 | 18.89 | 19.0 | 70.98 | |
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| 3.3873 | 5.0 | 2925 | 3.2867 | 21.47 | 9.0 | 19.54 | 19.0 | 71.23 | |
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| 3.3037 | 6.0 | 3510 | 3.2693 | 21.41 | 9.0 | 19.5 | 19.0 | 71.21 | |
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| 3.2357 | 7.0 | 4095 | 3.2581 | 22.05 | 9.36 | 20.04 | 19.0 | 71.43 | |
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| 3.1798 | 8.0 | 4680 | 3.2522 | 22.21 | 9.56 | 20.23 | 19.0 | 71.41 | |
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| 3.1359 | 9.0 | 5265 | 3.2546 | 22.27 | 9.58 | 20.23 | 19.0 | 71.46 | |
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| 3.0997 | 10.0 | 5850 | 3.2546 | 22.2 | 9.57 | 20.26 | 19.0 | 71.43 | |
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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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