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t5-small-destination-inference
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6668
- Rouge1: 25.6235
- Rouge2: 0.0
- Rougel: 25.6064
- Rougelsum: 25.6064
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.6932 | 1.0 | 2927 | 2.0668 | 19.9009 | 0.0 | 19.9009 | 19.8838 |
| 2.1793 | 2.0 | 5854 | 1.8923 | 22.2668 | 0.0 | 22.2583 | 22.2412 |
| 2.0209 | 3.0 | 8781 | 1.8088 | 23.1807 | 0.0 | 23.1893 | 23.1978 |
| 1.9254 | 4.0 | 11708 | 1.7439 | 24.5815 | 0.0 | 24.5815 | 24.5815 |
| 1.8585 | 5.0 | 14635 | 1.7105 | 24.7865 | 0.0 | 24.7865 | 24.7865 |
| 1.814 | 6.0 | 17562 | 1.6863 | 25.2989 | 0.0 | 25.316 | 25.2989 |
| 1.781 | 7.0 | 20489 | 1.6730 | 25.3844 | 0.0 | 25.3844 | 25.3502 |
| 1.7679 | 8.0 | 23416 | 1.6668 | 25.6235 | 0.0 | 25.6064 | 25.6064 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
