t5-small-finetuned-aspect_based_news_summary
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5400
- Rouge1: 51.9048
- Rouge2: 32.7805
- Rougel: 50.0061
- Rougelsum: 49.8124
- Gen Len: 17.1963
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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 120 | 1.6026 | 50.6671 | 31.3901 | 48.6643 | 48.6284 | 17.785 |
| No log | 2.0 | 240 | 1.5400 | 51.9048 | 32.7805 | 50.0061 | 49.8124 | 17.1963 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
google-t5/t5-small