tst-summarization
This model is a fine-tuned version of t5-small on the cnn_dailymail 3.0.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6418
- Rouge1: 41.607
- Rouge2: 19.2272
- Rougel: 29.4514
- Rougelsum: 38.8228
- Gen Len: 73.8731
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train sudoLife/tst-summarization
Evaluation results
- Rouge1 on cnn_dailymail 3.0.0validation set self-reported41.607