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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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+ - arabic
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+ - ar
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+ - mt5
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+ - Abstractive 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: mt5-base-finetuned-urdu-finetuned-urdu-arabic
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+ results: []
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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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+ # mt5-base-finetuned-urdu-finetuned-urdu-arabic
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+
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+ This model is a fine-tuned version of [eslamxm/mt5-base-finetuned-urdu](https://huggingface.co/eslamxm/mt5-base-finetuned-urdu) on the xlsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.3744
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+ - Rouge-1: 22.77
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+ - Rouge-2: 10.15
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+ - Rouge-l: 20.71
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+ - Gen Len: 19.0
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+ - Bertscore: 71.46
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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: 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: 8
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+ - total_train_batch_size: 32
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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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+ - num_epochs: 5
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+ - label_smoothing_factor: 0.1
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+
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+ ### Training results
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+
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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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+ | 4.5155 | 1.0 | 1172 | 3.6895 | 18.81 | 6.77 | 17.01 | 19.0 | 70.27 |
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+ | 3.8315 | 2.0 | 2344 | 3.5047 | 19.75 | 7.79 | 17.95 | 19.0 | 70.58 |
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+ | 3.6122 | 3.0 | 3516 | 3.4231 | 20.46 | 8.44 | 18.7 | 19.0 | 70.8 |
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+ | 3.4735 | 4.0 | 4688 | 3.3835 | 21.12 | 8.86 | 19.21 | 19.0 | 70.98 |
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+ | 3.3855 | 5.0 | 5860 | 3.3744 | 21.48 | 9.01 | 19.57 | 19.0 | 71.17 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.2.1
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+ - Tokenizers 0.12.1