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: 1.6033
- Rouge1: 0.2173
- Rouge2: 0.094
- Rougel: 0.1831
- Rougelsum: 0.183
- 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 | 1.6238 | 0.2169 | 0.0934 | 0.1821 | 0.1821 | 19.0 |
1.9204 | 2.0 | 862 | 1.6065 | 0.217 | 0.0937 | 0.1827 | 0.1826 | 19.0 |
1.8219 | 3.0 | 1293 | 1.6033 | 0.2173 | 0.094 | 0.1831 | 0.183 | 19.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for arv2023/cnn_news_summary_model_trained_on_reduced_data
Base model
google-t5/t5-small