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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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- generated_from_trainer
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datasets:
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- xsum
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metrics:
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- rouge
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model-index:
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- name: t5-small-finetuned-xsum
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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: xsum
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type: xsum
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config: default
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split: validation[:10%]
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args: default
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metrics:
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- name: Rouge1
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type: rouge
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value: 24.2894
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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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# t5-small-finetuned-xsum
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.6658
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- Rouge1: 24.2894
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- Rouge2: 5.5018
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- Rougel: 18.7615
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- Rougelsum: 18.7685
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- Gen Len: 18.6893
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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: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
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| 3.0564 | 0.78 | 500 | 2.6658 | 24.2894 | 5.5018 | 18.7615 | 18.7685 | 18.6893 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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