cnn_news_summary_model_trained_on_reduced_data
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5027
- Rouge1: 0.223
- Rouge2: 0.0955
- Rougel: 0.1859
- Rougelsum: 0.1859
- Gen Len: 19.9994
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | 1.5091 | 0.222 | 0.0954 | 0.1853 | 0.1854 | 19.9994 |
| 1.6772 | 2.0 | 862 | 1.5046 | 0.2223 | 0.0953 | 0.1854 | 0.1855 | 19.9994 |
| 1.6703 | 3.0 | 1293 | 1.5027 | 0.223 | 0.0955 | 0.1859 | 0.1859 | 19.9994 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0
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google-t5/t5-small