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: 1.6625
- Rouge1: 0.2171
- Rouge2: 0.0904
- Rougel: 0.1834
- Rougelsum: 0.1833
- 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|---|---|---|---|---|---|---|---|---|
| 1.984 | 1.0 | 574 | 1.6625 | 0.2171 | 0.0904 | 0.1834 | 0.1833 | 19.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Inference Providers
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Model tree for Musab-Bin-Nadeem/cnn_news_summary_model_trained_on_reduced_data
Base model
google-t5/t5-small