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README.md
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---
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license: apache-2.0
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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: distilbart-cnn-12-6-sec
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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-cnn-12-6-sec
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This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0798
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- Rouge1: 72.1665
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- Rouge2: 62.2601
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- Rougel: 67.8376
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- Rougelsum: 71.1407
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- Gen Len: 121.62
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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: 2
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- eval_batch_size: 2
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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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- 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 | 99 | 0.3526 | 53.3978 | 38.6395 | 45.6271 | 51.0477 | 111.48 |
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| No log | 2.0 | 198 | 0.1961 | 55.7397 | 43.6293 | 50.9595 | 54.0764 | 111.46 |
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| No log | 3.0 | 297 | 0.1483 | 66.9443 | 54.8966 | 62.6678 | 65.6787 | 118.64 |
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| No log | 4.0 | 396 | 0.1218 | 67.2661 | 56.1852 | 63.1339 | 65.8066 | 124.92 |
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| No log | 5.0 | 495 | 0.1139 | 67.2097 | 55.8694 | 62.7508 | 65.9706 | 123.02 |
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| 0.4156 | 6.0 | 594 | 0.0940 | 71.607 | 60.6697 | 66.7873 | 70.339 | 122.84 |
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| 0.4156 | 7.0 | 693 | 0.0888 | 71.3792 | 61.8326 | 68.25 | 70.5113 | 124.4 |
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| 0.4156 | 8.0 | 792 | 0.0870 | 72.7472 | 62.6968 | 68.2853 | 71.5789 | 124.34 |
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| 0.4156 | 9.0 | 891 | 0.0799 | 73.4438 | 63.5966 | 68.8737 | 72.3014 | 119.88 |
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| 0.4156 | 10.0 | 990 | 0.0798 | 72.1665 | 62.2601 | 67.8376 | 71.1407 | 121.62 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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