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t5-base-finetuned-noun_ellipse
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1470
- Rouge1: 95.8095
- Rouge2: 93.6
- Rougel: 95.8095
- Rougelsum: 95.8095
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: 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
No log | 1.0 | 50 | 0.1700 | 94.1905 | 90.0857 | 94.0952 | 94.0952 |
No log | 2.0 | 100 | 0.1500 | 94.9524 | 92.7429 | 95.1429 | 95.0 |
No log | 3.0 | 150 | 0.1476 | 95.8095 | 93.6 | 95.8095 | 95.8095 |
No log | 4.0 | 200 | 0.1480 | 95.8095 | 93.6 | 95.8095 | 95.8095 |
No log | 5.0 | 250 | 0.1470 | 95.8095 | 93.6 | 95.8095 | 95.8095 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2