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update model card README.md

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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: finetune-newwiki-summarization-ver1
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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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+ # finetune-newwiki-summarization-ver1
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+
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+ This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4720
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+ - Rouge1: 48.6293
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+ - Rouge2: 25.6053
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+ - Rougel: 35.2967
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+ - Rougelsum: 37.4842
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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: 1e-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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+ - 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: 0.05
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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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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+ | 0.7106 | 1.0 | 1980 | 0.5006 | 46.5921 | 22.8276 | 33.1994 | 35.6330 |
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+ | 0.621 | 2.0 | 3960 | 0.4774 | 47.4426 | 24.1508 | 34.1315 | 36.5692 |
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+ | 0.5607 | 3.0 | 5940 | 0.4690 | 48.1503 | 24.7217 | 34.5071 | 36.7568 |
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+ | 0.5241 | 4.0 | 7920 | 0.4673 | 48.2480 | 25.0604 | 34.4937 | 36.9301 |
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+ | 0.499 | 5.0 | 9900 | 0.4678 | 48.1659 | 25.1857 | 34.9460 | 37.1931 |
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+ | 0.4592 | 6.0 | 11880 | 0.4694 | 48.5839 | 25.5925 | 35.2301 | 37.5352 |
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+ | 0.4535 | 7.0 | 13860 | 0.4720 | 48.6293 | 25.6053 | 35.2967 | 37.4842 |
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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 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2