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--- |
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license: mit |
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base_model: facebook/bart-large-cnn |
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tags: |
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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: bart-large-cnn-finetuned-scope-summarization |
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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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# bart-large-cnn-finetuned-scope-summarization |
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0451 |
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- Rouge1: 50.5384 |
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- Rouge2: 38.354 |
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- Rougel: 39.3824 |
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- Rougelsum: 39.3274 |
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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: 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: 10 |
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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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| 0.4522 | 1.0 | 29 | 0.1016 | 39.3219 | 23.9312 | 30.059 | 30.0842 | |
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| 0.115 | 2.0 | 58 | 0.0910 | 42.5308 | 28.0438 | 34.7355 | 34.6854 | |
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| 0.1008 | 3.0 | 87 | 0.0773 | 46.8072 | 32.1794 | 38.8917 | 39.1092 | |
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| 0.0887 | 4.0 | 116 | 0.0748 | 40.6291 | 27.6322 | 31.1978 | 31.2266 | |
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| 0.0878 | 5.0 | 145 | 0.0678 | 45.3986 | 31.5703 | 35.6892 | 35.7214 | |
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| 0.077 | 6.0 | 174 | 0.0598 | 47.8845 | 34.9979 | 39.1758 | 39.3253 | |
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| 0.0714 | 7.0 | 203 | 0.0559 | 49.0723 | 35.9285 | 37.1426 | 37.1948 | |
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| 0.061 | 8.0 | 232 | 0.0509 | 49.7851 | 37.3486 | 40.8669 | 40.9567 | |
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| 0.0625 | 9.0 | 261 | 0.0465 | 50.7533 | 37.6276 | 39.9594 | 40.0946 | |
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| 0.0488 | 10.0 | 290 | 0.0451 | 50.5384 | 38.354 | 39.3824 | 39.3274 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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