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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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- cnn_dailymail
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metrics:
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- rouge
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model-index:
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- name: bart-finetuned-cnn-3
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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: cnn_dailymail
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type: cnn_dailymail
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args: 3.0.0
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metrics:
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- name: Rouge1
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type: rouge
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value: 40.201
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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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# bart-finetuned-cnn-3
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This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-3](https://huggingface.co/sshleifer/distilbart-xsum-12-3) on the cnn_dailymail dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0751
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- Rouge1: 40.201
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- Rouge2: 18.8482
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- Rougel: 29.4439
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- Rougelsum: 37.416
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- Gen Len: 56.7545
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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: 5e-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: 3
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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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| 2.276 | 1.0 | 8883 | 2.1762 | 39.6581 | 18.3333 | 28.7765 | 36.7688 | 58.5386 |
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| 2.0806 | 2.0 | 17766 | 2.0909 | 40.0328 | 18.8026 | 29.417 | 37.3508 | 56.6804 |
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| 1.9615 | 3.0 | 26649 | 2.0751 | 40.201 | 18.8482 | 29.4439 | 37.416 | 56.7545 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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