mt5-small-finetunedOn-OrangeSum-PT
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2710
- Rouge1: 0.2001
- Rouge2: 0.0581
- Rougel: 0.1688
- Rougelsum: 0.1695
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 |
---|---|---|---|---|---|---|---|
5.6747 | 1.0 | 625 | 2.5273 | 0.1978 | 0.0646 | 0.1656 | 0.1656 |
3.317 | 2.0 | 1250 | 2.4205 | 0.1933 | 0.0548 | 0.1591 | 0.1588 |
3.0952 | 3.0 | 1875 | 2.3493 | 0.1964 | 0.0555 | 0.1613 | 0.1619 |
2.9607 | 4.0 | 2500 | 2.3286 | 0.1927 | 0.0557 | 0.1644 | 0.1657 |
2.8771 | 5.0 | 3125 | 2.3064 | 0.1984 | 0.0559 | 0.1652 | 0.1661 |
2.8192 | 6.0 | 3750 | 2.2847 | 0.1960 | 0.0546 | 0.1641 | 0.1647 |
2.7852 | 7.0 | 4375 | 2.2720 | 0.1989 | 0.0588 | 0.1692 | 0.1701 |
2.7691 | 8.0 | 5000 | 2.2710 | 0.2001 | 0.0581 | 0.1688 | 0.1695 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.13.1
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