cnn_news_summary_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6031
- Rouge1: 0.2232
- Rouge2: 0.0962
- Rougel: 0.1868
- Rougelsum: 0.1867
- Gen Len: 20.0
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: Use OptimizerNames.ADAMW_TORCH_FUSED 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 | 1.6228 | 0.224 | 0.0966 | 0.1865 | 0.1864 | 20.0 |
| 1.9211 | 2.0 | 862 | 1.6075 | 0.2238 | 0.0964 | 0.1868 | 0.1868 | 20.0 |
| 1.8222 | 3.0 | 1293 | 1.6031 | 0.2232 | 0.0962 | 0.1868 | 0.1867 | 20.0 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Base model
google-t5/t5-small