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--- |
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library_name: transformers |
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license: bsd-3-clause |
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base_model: pszemraj/led-base-book-summary |
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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: LED-cnn-dataset-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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# LED-cnn-dataset-summarization |
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This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co/pszemraj/led-base-book-summary) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0098 |
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- Rouge1: 0.4061 |
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- Rouge2: 0.1676 |
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- Rougel: 0.2695 |
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- Rougelsum: 0.3756 |
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- Gen Len: 79.036 |
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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: 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: 8 |
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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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| No log | 1.0 | 250 | 1.8883 | 0.4074 | 0.1733 | 0.2733 | 0.3741 | 81.696 | |
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| 1.9196 | 2.0 | 500 | 1.8782 | 0.4105 | 0.1738 | 0.2735 | 0.3789 | 85.312 | |
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| 1.9196 | 3.0 | 750 | 1.8763 | 0.408 | 0.1734 | 0.2747 | 0.3754 | 84.348 | |
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| 1.4188 | 4.0 | 1000 | 1.9043 | 0.4086 | 0.1716 | 0.273 | 0.3795 | 79.842 | |
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| 1.4188 | 5.0 | 1250 | 1.9344 | 0.4084 | 0.1686 | 0.2713 | 0.377 | 79.926 | |
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| 1.168 | 6.0 | 1500 | 1.9623 | 0.4121 | 0.1733 | 0.2749 | 0.3813 | 77.228 | |
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| 1.168 | 7.0 | 1750 | 2.0004 | 0.4092 | 0.1711 | 0.273 | 0.3794 | 77.102 | |
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| 1.0279 | 8.0 | 2000 | 2.0098 | 0.4061 | 0.1676 | 0.2695 | 0.3756 | 79.036 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.19.1 |
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