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pegasus-xsum_summarization

Transformers
PyTorch
pegasus
text2text-generation
Generated from Trainer
Model card Files
xet
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update model card README.md

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  ---
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: pegasus-xsum_summarization
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  results: []
@@ -13,7 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9498
 
 
 
 
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 3.4508 | 1.0 | 50 | 2.5701 |
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- | 2.655 | 2.0 | 100 | 2.2977 |
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- | 2.3635 | 3.0 | 150 | 2.1554 |
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- | 2.0941 | 4.0 | 200 | 2.0545 |
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- | 2.0085 | 5.0 | 250 | 2.0147 |
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- | 1.8447 | 6.0 | 300 | 1.9754 |
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- | 1.7749 | 7.0 | 350 | 1.9592 |
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- | 1.7061 | 8.0 | 400 | 1.9498 |
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  ### Framework versions
 
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  ---
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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: pegasus-xsum_summarization
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  results: []
 
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  This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7876
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+ - Rouge1: 25.7148
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+ - Rouge2: 10.9685
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+ - Rougel: 21.6394
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+ - Rougelsum: 22.3122
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  ## Model description
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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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+ | 1.633 | 1.0 | 50 | 1.8839 | 24.9703 | 9.6517 | 19.9759 | 21.088 |
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+ | 1.3917 | 2.0 | 100 | 1.8565 | 24.4395 | 9.1755 | 19.5702 | 20.5489 |
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+ | 1.2576 | 3.0 | 150 | 1.8361 | 24.8266 | 10.2009 | 20.074 | 21.382 |
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+ | 1.1191 | 4.0 | 200 | 1.8226 | 25.9635 | 11.7704 | 21.7787 | 22.365 |
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+ | 1.1138 | 5.0 | 250 | 1.8239 | 26.7874 | 12.2832 | 22.7792 | 23.4501 |
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+ | 1.0338 | 6.0 | 300 | 1.8094 | 26.3543 | 12.0501 | 22.3172 | 23.1194 |
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+ | 1.0084 | 7.0 | 350 | 1.7923 | 25.5686 | 11.0213 | 21.5288 | 21.8892 |
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+ | 1.0098 | 8.0 | 400 | 1.7876 | 25.7148 | 10.9685 | 21.6394 | 22.3122 |
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  ### Framework versions