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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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metrics: |
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- rouge |
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model-index: |
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- name: AraBART-finetuned-ar |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: xlsum |
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type: xlsum |
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args: arabic |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 2.2459 |
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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: 2.3785 |
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- Rouge1: 2.2459 |
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- Rouge2: 0.0 |
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- Rougel: 2.2459 |
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- Rougelsum: 2.2459 |
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- Gen Len: 19.695 |
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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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- 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_ratio: 0.6 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 0.98 | 32 | 2.7774 | 1.0638 | 0.0 | 1.0638 | 1.182 | 19.5177 | |
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| No log | 1.98 | 64 | 2.4730 | 1.182 | 0.0 | 1.3002 | 1.182 | 19.8121 | |
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| No log | 2.98 | 96 | 2.4129 | 2.3641 | 0.3546 | 2.3641 | 2.3641 | 19.8298 | |
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| No log | 3.98 | 128 | 2.3724 | 2.1277 | 0.3546 | 2.1277 | 2.1277 | 19.8121 | |
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| No log | 4.98 | 160 | 2.3560 | 1.8913 | 0.3546 | 1.8913 | 1.8913 | 19.805 | |
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| No log | 5.98 | 192 | 2.3574 | 1.5366 | 0.0 | 1.5366 | 1.6548 | 19.7979 | |
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| No log | 6.98 | 224 | 2.3676 | 2.1277 | 0.3546 | 2.2459 | 2.1277 | 19.6348 | |
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| No log | 7.98 | 256 | 2.3656 | 2.0095 | 0.0 | 2.0095 | 2.0095 | 19.844 | |
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| No log | 8.98 | 288 | 2.3751 | 2.2459 | 0.0 | 2.3641 | 2.2459 | 19.6738 | |
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| No log | 9.98 | 320 | 2.3785 | 2.2459 | 0.0 | 2.2459 | 2.2459 | 19.695 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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