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mt5-small-finetuned-13feb-6
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: 2.4645
- Rouge1: 18.09
- Rouge2: 5.09
- Rougel: 17.85
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: 5e-05
- 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: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 7.2878 | 1.0 | 311 | 2.8276 | 8.04 | 2.25 | 7.88 |
| 3.6569 | 2.0 | 622 | 2.6625 | 15.73 | 4.67 | 15.52 |
| 3.3882 | 3.0 | 933 | 2.5924 | 16.9 | 5.12 | 16.63 |
| 3.2381 | 4.0 | 1244 | 2.5561 | 17.23 | 5.44 | 17.01 |
| 3.1386 | 5.0 | 1555 | 2.5301 | 16.92 | 5.16 | 16.69 |
| 3.0852 | 6.0 | 1866 | 2.5098 | 17.46 | 5.18 | 17.25 |
| 3.0244 | 7.0 | 2177 | 2.4873 | 17.48 | 5.05 | 17.23 |
| 2.9948 | 8.0 | 2488 | 2.4817 | 18.26 | 5.31 | 17.96 |
| 2.9542 | 9.0 | 2799 | 2.4892 | 17.97 | 5.5 | 17.68 |
| 2.9376 | 10.0 | 3110 | 2.4708 | 17.58 | 5.03 | 17.31 |
| 2.9197 | 11.0 | 3421 | 2.4697 | 18.05 | 5.05 | 17.75 |
| 2.9126 | 12.0 | 3732 | 2.4645 | 18.09 | 5.09 | 17.85 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
