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mt5-small-text-sum-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: 2.3694
- Rouge1: 20.18
- Rouge2: 6.52
- 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: 12
- eval_batch_size: 12
- 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 |
|---|---|---|---|---|---|---|
| 4.4337 | 1.93 | 500 | 2.5989 | 15.94 | 4.85 | 15.78 |
| 3.0621 | 3.86 | 1000 | 2.4750 | 19.09 | 5.95 | 18.82 |
| 2.8411 | 5.79 | 1500 | 2.4011 | 18.39 | 5.69 | 18.22 |
| 2.6947 | 7.72 | 2000 | 2.3851 | 19.27 | 5.79 | 19.01 |
| 2.5872 | 9.65 | 2500 | 2.3918 | 19.09 | 6.02 | 18.81 |
| 2.4996 | 11.58 | 3000 | 2.3689 | 18.84 | 5.84 | 18.46 |
| 2.4192 | 13.51 | 3500 | 2.3604 | 19.89 | 5.97 | 19.5 |
| 2.3524 | 15.44 | 4000 | 2.3694 | 20.18 | 6.52 | 19.84 |
| 2.3012 | 17.37 | 4500 | 2.3637 | 19.24 | 5.51 | 18.9 |
| 2.2408 | 19.31 | 5000 | 2.3374 | 19.78 | 6.27 | 19.43 |
| 2.2004 | 21.24 | 5500 | 2.3400 | 19.74 | 6.06 | 19.37 |
| 2.1631 | 23.17 | 6000 | 2.3584 | 19.95 | 6.08 | 19.53 |
| 2.123 | 25.1 | 6500 | 2.3527 | 19.64 | 5.9 | 19.36 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
