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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: AraT5-base-title-generation-finetuned-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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# AraT5-base-title-generation-finetuned-ar-xlsum |
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This model is a fine-tuned version of [UBC-NLP/AraT5-base-title-generation](https://huggingface.co/UBC-NLP/AraT5-base-title-generation) on the wiki_lingua dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.8120 |
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- Rouge-1: 23.29 |
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- Rouge-2: 8.44 |
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- Rouge-l: 20.74 |
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- Gen Len: 18.16 |
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- Bertscore: 70.88 |
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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: 5e-05 |
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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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| 6.1002 | 1.0 | 5111 | 5.2917 | 18.95 | 5.84 | 17.01 | 17.9 | 68.69 | |
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| 5.4427 | 2.0 | 10222 | 5.0877 | 20.61 | 6.73 | 18.58 | 17.14 | 69.69 | |
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| 5.1876 | 3.0 | 15333 | 4.9631 | 21.27 | 7.17 | 19.09 | 17.69 | 69.82 | |
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| 5.0256 | 4.0 | 20444 | 4.8984 | 21.7 | 7.53 | 19.55 | 17.56 | 70.18 | |
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| 4.9104 | 5.0 | 25555 | 4.8538 | 22.23 | 7.54 | 19.79 | 17.6 | 70.33 | |
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| 4.8251 | 6.0 | 30666 | 4.8309 | 22.35 | 7.6 | 19.96 | 17.64 | 70.51 | |
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| 4.7666 | 7.0 | 35777 | 4.8168 | 22.45 | 7.81 | 20.15 | 17.47 | 70.61 | |
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| 4.7275 | 8.0 | 40888 | 4.8120 | 22.67 | 7.83 | 20.34 | 17.56 | 70.66 | |
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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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