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mt5-small-finetuned-31jan-4
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5165
- Rouge1: 19.31
- Rouge2: 6.34
- Rougel: 19.06
- Rougelsum: 19.09
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: 0.0001
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
6.4223 | 1.0 | 217 | 2.8162 | 13.51 | 3.46 | 13.13 | 13.26 |
3.4986 | 2.0 | 434 | 2.7158 | 15.95 | 4.09 | 15.66 | 15.77 |
3.2297 | 3.0 | 651 | 2.6552 | 16.82 | 4.3 | 16.4 | 16.52 |
3.0796 | 4.0 | 868 | 2.6526 | 17.99 | 5.02 | 17.6 | 17.79 |
2.969 | 5.0 | 1085 | 2.6005 | 18.05 | 5.22 | 17.78 | 17.79 |
2.8939 | 6.0 | 1302 | 2.5879 | 18.22 | 5.17 | 17.93 | 18.01 |
2.8147 | 7.0 | 1519 | 2.5569 | 18.25 | 5.56 | 18.03 | 18.14 |
2.7642 | 8.0 | 1736 | 2.5541 | 18.24 | 5.38 | 18.07 | 18.19 |
2.724 | 9.0 | 1953 | 2.5493 | 18.86 | 5.7 | 18.51 | 18.63 |
2.6962 | 10.0 | 2170 | 2.5320 | 19.12 | 5.72 | 18.93 | 19.01 |
2.6499 | 11.0 | 2387 | 2.5224 | 18.78 | 5.69 | 18.6 | 18.66 |
2.6242 | 12.0 | 2604 | 2.5272 | 19.23 | 5.82 | 18.96 | 18.99 |
2.6088 | 13.0 | 2821 | 2.5122 | 19.51 | 6.16 | 19.26 | 19.36 |
2.5976 | 14.0 | 3038 | 2.5218 | 19.06 | 6.23 | 18.82 | 18.87 |
2.5775 | 15.0 | 3255 | 2.5165 | 19.31 | 6.34 | 19.06 | 19.09 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2