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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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- summarization
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- generated_from_trainer
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datasets:
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- cnn_dailymail
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metrics:
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- rouge
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model-index:
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- name: t5-small-finetuned-cnn
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results:
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- task:
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name: Sequence-to-sequence Language Modeling
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type: text2text-generation
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dataset:
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name: cnn_dailymail
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type: cnn_dailymail
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args: 3.0.0
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metrics:
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- name: Rouge1
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type: rouge
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value: 33.2082
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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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# t5-small-finetuned-cnn
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8436
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- Rouge1: 33.2082
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- Rouge2: 16.798
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- Rougel: 28.9573
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- Rougelsum: 31.1044
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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: 8
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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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| 2.3793 | 1.0 | 359 | 1.8885 | 33.0321 | 16.7798 | 28.9367 | 30.9509 |
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| 2.1432 | 2.0 | 718 | 1.8481 | 33.1559 | 16.8557 | 29.015 | 31.1122 |
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| 2.0571 | 3.0 | 1077 | 1.8391 | 32.99 | 16.716 | 28.8118 | 30.9178 |
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| 2.0001 | 4.0 | 1436 | 1.8357 | 33.0543 | 16.6731 | 28.8375 | 30.9604 |
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| 1.9609 | 5.0 | 1795 | 1.8437 | 33.1019 | 16.7576 | 28.8669 | 31.001 |
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| 1.925 | 6.0 | 2154 | 1.8402 | 33.1388 | 16.7539 | 28.8887 | 31.0262 |
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| 1.9036 | 7.0 | 2513 | 1.8423 | 33.1825 | 16.759 | 28.9154 | 31.0656 |
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| 1.8821 | 8.0 | 2872 | 1.8436 | 33.2082 | 16.798 | 28.9573 | 31.1044 |
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### Framework versions
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- Transformers 4.14.0
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- Pytorch 1.5.0
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- Datasets 2.3.2
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- Tokenizers 0.10.3
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