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--- |
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license: apache-2.0 |
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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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- xlsum |
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model-index: |
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- name: AraBART-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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# AraBART-finetuned-ar |
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This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7449 |
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- Rouge-1: 31.08 |
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- Rouge-2: 14.68 |
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- Rouge-l: 27.36 |
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- Gen Len: 19.64 |
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- Bertscore: 73.86 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 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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| 4.4318 | 1.0 | 2345 | 3.7996 | 28.93 | 13.2 | 25.56 | 19.51 | 73.17 | |
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| 4.0338 | 2.0 | 4690 | 3.7483 | 30.29 | 14.24 | 26.73 | 19.5 | 73.59 | |
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| 3.8586 | 3.0 | 7035 | 3.7281 | 30.44 | 14.44 | 26.92 | 19.75 | 73.58 | |
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| 3.7289 | 4.0 | 9380 | 3.7204 | 30.55 | 14.49 | 26.88 | 19.66 | 73.73 | |
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| 3.6245 | 5.0 | 11725 | 3.7199 | 30.73 | 14.63 | 27.11 | 19.69 | 73.68 | |
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| 3.5392 | 6.0 | 14070 | 3.7221 | 30.85 | 14.65 | 27.21 | 19.7 | 73.77 | |
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| 3.4694 | 7.0 | 16415 | 3.7286 | 31.08 | 14.8 | 27.41 | 19.62 | 73.84 | |
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| 3.4126 | 8.0 | 18760 | 3.7384 | 31.06 | 14.77 | 27.41 | 19.64 | 73.82 | |
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| 3.3718 | 9.0 | 21105 | 3.7398 | 31.18 | 14.89 | 27.49 | 19.67 | 73.87 | |
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| 3.3428 | 10.0 | 23450 | 3.7449 | 31.19 | 14.88 | 27.44 | 19.68 | 73.87 | |
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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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