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--- |
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license: apache-2.0 |
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base_model: facebook/bart-base |
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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: bart-base-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: train[: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: 35.8214 |
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pipeline_tag: summarization |
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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-xsum |
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9356 |
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- Rouge1: 35.8214 |
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- Rouge2: 14.7565 |
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- Rougel: 29.4566 |
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- Rougelsum: 29.4496 |
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- Gen Len: 19.562 |
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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: 16 |
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- eval_batch_size: 16 |
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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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- 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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| 2.301 | 1.0 | 1148 | 1.9684 | 34.4715 | 13.6638 | 28.1147 | 28.1204 | 19.5816 | |
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| 2.1197 | 2.0 | 2296 | 1.9442 | 35.2502 | 14.284 | 28.8462 | 28.8384 | 19.5546 | |
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| 1.9804 | 3.0 | 3444 | 1.9406 | 35.7799 | 14.7422 | 29.3669 | 29.3742 | 19.5326 | |
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| 1.8891 | 4.0 | 4592 | 1.9349 | 35.5151 | 14.4668 | 29.0359 | 29.0484 | 19.5492 | |
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| 1.827 | 5.0 | 5740 | 1.9356 | 35.8214 | 14.7565 | 29.4566 | 29.4496 | 19.562 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
