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--- |
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license: apache-2.0 |
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tags: |
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- summarisation |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: distilbart-xsum-6-6-finetuned-bbc-news-on-abstractive |
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results: [] |
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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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# distilbart-xsum-6-6-finetuned-bbc-news-on-abstractive |
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This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/sshleifer/distilbart-xsum-6-6) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6549 |
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- Rouge1: 38.9186 |
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- Rouge2: 30.2223 |
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- Rougel: 32.6201 |
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- Rougelsum: 37.7502 |
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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: 5.6e-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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- 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: 4 |
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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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| 1.3838 | 1.0 | 445 | 1.4841 | 39.1621 | 30.4379 | 32.6613 | 37.9963 | |
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| 1.0077 | 2.0 | 890 | 1.5173 | 39.388 | 30.9125 | 33.099 | 38.2442 | |
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| 0.7983 | 3.0 | 1335 | 1.5726 | 38.7913 | 30.0766 | 32.6092 | 37.5953 | |
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| 0.6681 | 4.0 | 1780 | 1.6549 | 38.9186 | 30.2223 | 32.6201 | 37.7502 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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