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update model card README.md

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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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+ - fa
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+ - persian
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+ - mt5
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+ - Abstractive Summarization
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+ - generated_from_trainer
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+ model-index:
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+ - name: mt5-base-finetuned-ar-fa
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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-ar-fa
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+
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+ This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.0303
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+ - Rouge-1: 26.73
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+ - Rouge-2: 12.63
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+ - Rouge-l: 23.96
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+ - Gen Len: 18.99
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+ - Bertscore: 71.41
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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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+ | 3.7736 | 1.0 | 3287 | 3.2308 | 24.22 | 10.11 | 21.46 | 18.99 | 70.69 |
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+ | 3.3783 | 2.0 | 6574 | 3.1283 | 25.28 | 10.9 | 22.43 | 18.99 | 71.02 |
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+ | 3.2351 | 3.0 | 9861 | 3.0693 | 25.77 | 11.36 | 22.93 | 19.0 | 71.2 |
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+ | 3.1363 | 4.0 | 13148 | 3.0421 | 25.88 | 11.57 | 23.08 | 18.99 | 71.22 |
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+ | 3.0669 | 5.0 | 16435 | 3.0303 | 26.25 | 11.84 | 23.44 | 18.99 | 71.39 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.2.2
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+ - Tokenizers 0.12.1