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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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+ - generated_from_trainer
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+ datasets:
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+ - wiki_lingua
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: wiki_lingua-fr-8-3-5.6e-05-mt5-small-finetuned
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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: wiki_lingua
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+ type: wiki_lingua
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+ config: fr
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+ split: test
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+ args: fr
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+ metrics:
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+ - name: Rouge1
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+ type: rouge
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+ value: 19.9596
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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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+ # wiki_lingua-fr-8-3-5.6e-05-mt5-small-finetuned
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+
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+ This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the wiki_lingua dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9117
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+ - Rouge1: 19.9596
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+ - Rouge2: 7.5052
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+ - Rougel: 17.4363
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+ - Rougelsum: 19.5192
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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: 5.6e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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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+ - num_epochs: 3
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
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+ | 2.8962 | 1.0 | 5428 | 2.0026 | 18.8621 | 6.6127 | 16.0264 | 18.4354 |
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+ | 2.313 | 2.0 | 10856 | 1.9260 | 19.7274 | 7.2791 | 17.0466 | 19.2904 |
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+ | 2.2248 | 3.0 | 16284 | 1.9117 | 19.9596 | 7.5052 | 17.4363 | 19.5192 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.4
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+ - Pytorch 1.13.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.2