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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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- cnn_dailymail |
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metrics: |
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- rouge |
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model-index: |
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- name: bart-base-finetuned-cnn-news |
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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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config: 3.0.0 |
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split: validation |
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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: 21.8948 |
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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-base-finetuned-cnn-news |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the cnn_dailymail dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8560 |
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- Rouge1: 21.8948 |
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- Rouge2: 9.7157 |
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- Rougel: 17.9348 |
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- Rougelsum: 20.5347 |
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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: 0.00056 |
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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: 5 |
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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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| 3.7005 | 1.0 | 718 | 2.9872 | 21.7279 | 9.0406 | 17.392 | 20.0627 | |
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| 2.937 | 2.0 | 1436 | 2.8590 | 21.3056 | 8.5254 | 17.2338 | 20.0403 | |
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| 2.2642 | 3.0 | 2154 | 2.6744 | 21.277 | 9.6162 | 17.7775 | 20.1688 | |
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| 1.5774 | 4.0 | 2872 | 2.7020 | 21.7458 | 9.846 | 18.1649 | 20.7067 | |
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| 1.0174 | 5.0 | 3590 | 2.8560 | 21.8948 | 9.7157 | 17.9348 | 20.5347 | |
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### Framework versions |
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- Transformers 4.27.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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