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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-id-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: id
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split: test
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args: id
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metrics:
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- name: Rouge1
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type: rouge
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value: 18.0064
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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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# wiki_lingua-id-8-3-5.6e-05-mt5-small-finetuned
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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: 2.3388
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- Rouge1: 18.0064
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- Rouge2: 5.5315
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- Rougel: 16.1048
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- Rougelsum: 17.6763
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
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| 3.4701 | 1.0 | 4029 | 2.4403 | 17.0314 | 5.0932 | 15.3277 | 16.713 |
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| 2.8067 | 2.0 | 8058 | 2.3568 | 17.6738 | 5.3508 | 15.8002 | 17.336 |
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| 2.7095 | 3.0 | 12087 | 2.3388 | 18.0064 | 5.5315 | 16.1048 | 17.6763 |
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### Framework versions
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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
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