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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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datasets:
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- samsum
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metrics:
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- rouge
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model-index:
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- name: bart-large-xsum-finetuned-samsum-v2
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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: samsum
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type: samsum
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config: samsum
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split: train
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args: samsum
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metrics:
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- name: Rouge1
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type: rouge
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value: 54.1988
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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-large-xsum-finetuned-samsum-v2
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This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on the samsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4078
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- Rouge1: 54.1988
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- Rouge2: 29.3478
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- Rougel: 44.6308
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- Rougelsum: 49.8443
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- Gen Len: 29.0538
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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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| 1.3515 | 1.0 | 1841 | 1.4078 | 54.1988 | 29.3478 | 44.6308 | 49.8443 | 29.0538 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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