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cnn_news_summary_model_trained_on_reduced_data
This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.5899
- Rouge1: 0.2176
- Rouge2: 0.0942
- Rougel: 0.1832
- Rougelsum: 0.1828
- Gen Len: 19.0
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 431 | 1.5995 | 0.2168 | 0.0933 | 0.1824 | 0.1823 | 19.0 |
1.7979 | 2.0 | 862 | 1.5925 | 0.2177 | 0.0942 | 0.1835 | 0.1832 | 19.0 |
1.7936 | 3.0 | 1293 | 1.5899 | 0.2176 | 0.0942 | 0.1832 | 0.1828 | 19.0 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3