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README.md
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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-large-finetuned-rahulver-summarization-pegasus-model
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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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# pegasus-large-finetuned-rahulver-summarization-pegasus-model
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This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0906
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- Rouge1: 61.2393
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- Rouge2: 43.8277
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- Rougel: 50.0054
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- Rougelsum: 57.4674
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- Gen Len: 114.6
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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: 1
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- eval_batch_size: 1
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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 | Gen Len |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
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| 1.3648 | 1.0 | 140 | 0.7201 | 50.0081 | 32.6454 | 39.3021 | 45.1602 | 125.7333 |
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| 0.8502 | 2.0 | 280 | 0.6067 | 57.8678 | 41.5251 | 46.0694 | 54.1055 | 128.3333 |
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| 0.5053 | 3.0 | 420 | 0.6642 | 58.3644 | 41.8619 | 47.6199 | 54.1639 | 108.9667 |
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| 0.3469 | 4.0 | 560 | 0.7318 | 61.8988 | 45.7303 | 51.1928 | 57.9306 | 123.1667 |
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| 0.2779 | 5.0 | 700 | 0.7274 | 62.9354 | 46.5 | 51.6431 | 59.2443 | 99.6333 |
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| 0.2124 | 6.0 | 840 | 0.8618 | 63.8552 | 48.3846 | 53.3804 | 60.2718 | 111.2333 |
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| 0.1864 | 7.0 | 980 | 1.0058 | 59.5675 | 42.4324 | 48.462 | 55.3498 | 108.4667 |
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| 0.1691 | 8.0 | 1120 | 0.9984 | 60.1063 | 43.6022 | 49.7163 | 56.9865 | 130.2 |
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| 0.1603 | 9.0 | 1260 | 1.0062 | 61.398 | 44.4507 | 50.2044 | 57.4447 | 99.0333 |
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| 0.1674 | 10.0 | 1400 | 1.0906 | 61.2393 | 43.8277 | 50.0054 | 57.4674 | 114.6 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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