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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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- samsum
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metrics:
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- rouge
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model-index:
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- name: bart-samsung-5
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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: 48.4734
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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-samsung-5
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the samsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4959
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- Rouge1: 48.4734
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- Rouge2: 25.3475
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- Rougel: 40.9144
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- Rougelsum: 44.7797
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- Gen Len: 18.22
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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: 5
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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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| 1.6107 | 1.0 | 1841 | 1.5390 | 47.1407 | 24.384 | 40.4826 | 43.4437 | 17.5513 |
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| 1.5528 | 2.0 | 3682 | 1.4971 | 48.5483 | 25.1562 | 41.1806 | 44.7254 | 18.3521 |
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| 1.4225 | 3.0 | 5523 | 1.5013 | 48.2461 | 25.2181 | 40.9022 | 44.4942 | 18.0844 |
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| 1.3266 | 4.0 | 7364 | 1.4976 | 48.8949 | 25.4367 | 41.2355 | 45.0961 | 18.2359 |
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| 1.2635 | 5.0 | 9205 | 1.4959 | 48.4734 | 25.3475 | 40.9144 | 44.7797 | 18.22 |
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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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