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: 1.5909
- Rouge1: 0.2179
- Rouge2: 0.0947
- Rougel: 0.1841
- Rougelsum: 0.1841
- 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: Use 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 | Generated Length |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 431 | 1.6028 | 0.2178 | 0.0946 | 0.1837 | 0.1837 | 19.0 |
| 1.8071 | 2.0 | 862 | 1.5929 | 0.2172 | 0.0946 | 0.1835 | 0.1836 | 19.0 |
| 1.7953 | 3.0 | 1293 | 1.5909 | 0.2179 | 0.0947 | 0.1841 | 0.1841 | 19.0 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-t5/t5-small