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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-news |
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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: validation |
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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: 23.5402 |
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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-news |
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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: 2.7209 |
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- Rouge1: 23.5402 |
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- Rouge2: 10.8834 |
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- Rougel: 19.3936 |
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- Rougelsum: 22.1513 |
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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: 0.00056 |
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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: 5 |
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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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| 2.2531 | 1.0 | 718 | 2.6722 | 23.3437 | 10.5433 | 19.2183 | 21.8989 | |
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| 2.1518 | 2.0 | 1436 | 2.7024 | 23.4068 | 10.716 | 19.0751 | 21.9328 | |
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| 2.0925 | 3.0 | 2154 | 2.7235 | 23.232 | 10.5236 | 19.2254 | 21.8598 | |
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| 2.0808 | 4.0 | 2872 | 2.7309 | 23.7401 | 10.7664 | 19.4651 | 22.2479 | |
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| 2.1114 | 5.0 | 3590 | 2.7209 | 23.5402 | 10.8834 | 19.3936 | 22.1513 | |
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### Framework versions |
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- Transformers 4.27.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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