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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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+
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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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+
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+ # AraBART-finetuned-ar
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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