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mt5-small-text-sum-11
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: 2.3761
- Rouge1: 20.13
- Rouge2: 6.41
- Rougel: 19.84
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: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 4.558 | 1.45 | 500 | 2.6110 | 16.89 | 4.81 | 16.86 |
| 3.1188 | 2.9 | 1000 | 2.5397 | 17.58 | 5.27 | 17.4 |
| 2.8995 | 4.35 | 1500 | 2.4761 | 18.14 | 5.11 | 17.9 |
| 2.7608 | 5.8 | 2000 | 2.4130 | 18.52 | 4.95 | 18.15 |
| 2.644 | 7.25 | 2500 | 2.4375 | 18.82 | 5.25 | 18.51 |
| 2.5836 | 8.7 | 3000 | 2.4034 | 19.18 | 5.54 | 18.89 |
| 2.4949 | 10.14 | 3500 | 2.3703 | 19.4 | 5.84 | 18.98 |
| 2.4081 | 11.59 | 4000 | 2.3847 | 19.93 | 6.13 | 19.56 |
| 2.358 | 13.04 | 4500 | 2.3528 | 19.98 | 5.84 | 19.62 |
| 2.2951 | 14.49 | 5000 | 2.3611 | 20.46 | 6.11 | 20.06 |
| 2.2582 | 15.94 | 5500 | 2.3607 | 19.98 | 5.53 | 19.57 |
| 2.2157 | 17.39 | 6000 | 2.3763 | 19.69 | 5.61 | 19.43 |
| 2.1741 | 18.84 | 6500 | 2.3557 | 20.42 | 6.11 | 20.03 |
| 2.1302 | 20.29 | 7000 | 2.3623 | 19.44 | 5.53 | 18.99 |
| 2.1018 | 21.74 | 7500 | 2.3761 | 20.13 | 6.41 | 19.84 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2
