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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-summarization-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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config: 3.0.0
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split: train[:2%]
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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: 24.4825
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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-summarization-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: 2.0105
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- Rouge1: 24.4825
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- Rouge2: 9.1573
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- Rougel: 19.7135
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- Rougelsum: 22.2551
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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: 2
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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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| 2.0389 | 1.0 | 718 | 2.0150 | 24.4413 | 9.1782 | 19.7202 | 22.2225 |
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| 1.9497 | 2.0 | 1436 | 2.0105 | 24.4825 | 9.1573 | 19.7135 | 22.2551 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.0
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- Tokenizers 0.13.2
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