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: 1.6040
- Rouge1: 0.2181
- Rouge2: 0.0943
- Rougel: 0.184
- Rougelsum: 0.1838
- Generated Length: 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 | Generated Length |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 431 | 1.6222 | 0.2178 | 0.0936 | 0.1828 | 0.1827 | 19.0 |
| 1.9218 | 2.0 | 862 | 1.6069 | 0.2177 | 0.0939 | 0.1835 | 0.1834 | 19.0 |
| 1.8271 | 3.0 | 1293 | 1.6040 | 0.2181 | 0.0943 | 0.184 | 0.1838 | 19.0 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
google-t5/t5-small