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--- |
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license: apache-2.0 |
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tags: |
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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-cnndm1 |
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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: 24.4246 |
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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-cnndm1 |
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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: 1.6853 |
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- Rouge1: 24.4246 |
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- Rouge2: 11.6944 |
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- Rougel: 20.1717 |
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- Rougelsum: 23.0424 |
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- Gen Len: 18.9996 |
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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: 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: 1 |
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- mixed_precision_training: Native AMP |
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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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| 1.912 | 0.14 | 5000 | 1.7167 | 24.4232 | 11.7049 | 20.1758 | 23.0345 | 18.9997 | |
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| 1.8784 | 0.28 | 10000 | 1.7018 | 24.4009 | 11.6918 | 20.1561 | 23.0073 | 18.9997 | |
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| 1.8628 | 0.42 | 15000 | 1.6934 | 24.385 | 11.683 | 20.1285 | 22.9823 | 18.9997 | |
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| 1.8594 | 0.56 | 20000 | 1.6902 | 24.4407 | 11.6835 | 20.1734 | 23.0369 | 18.9996 | |
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| 1.8537 | 0.7 | 25000 | 1.6864 | 24.3635 | 11.658 | 20.1318 | 22.9782 | 18.9993 | |
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| 1.8505 | 0.84 | 30000 | 1.6856 | 24.4267 | 11.6991 | 20.1629 | 23.0361 | 18.9994 | |
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| 1.8505 | 0.98 | 35000 | 1.6853 | 24.4246 | 11.6944 | 20.1717 | 23.0424 | 18.9996 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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