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mt5-small-text-sum-7
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: 2.3801
- Rouge1: 20.58
- Rouge2: 6.51
- Rougel: 20.26
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: 13
- eval_batch_size: 13
- 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 |
|---|---|---|---|---|---|---|
| 4.4436 | 2.09 | 500 | 2.5528 | 17.73 | 5.9 | 17.55 |
| 3.0439 | 4.18 | 1000 | 2.4974 | 18.76 | 5.73 | 18.64 |
| 2.822 | 6.28 | 1500 | 2.4043 | 17.82 | 5.09 | 17.68 |
| 2.6799 | 8.37 | 2000 | 2.3938 | 18.9 | 5.73 | 18.62 |
| 2.5687 | 10.46 | 2500 | 2.3617 | 19.0 | 5.76 | 18.73 |
| 2.4701 | 12.55 | 3000 | 2.3455 | 19.82 | 6.14 | 19.54 |
| 2.3917 | 14.64 | 3500 | 2.3801 | 20.58 | 6.51 | 20.26 |
| 2.3427 | 16.74 | 4000 | 2.3407 | 19.52 | 6.49 | 19.23 |
| 2.2811 | 18.83 | 4500 | 2.3544 | 18.82 | 5.75 | 18.43 |
| 2.2347 | 20.92 | 5000 | 2.3503 | 20.17 | 6.08 | 19.76 |
| 2.1884 | 23.01 | 5500 | 2.3586 | 20.25 | 6.06 | 19.9 |
| 2.1414 | 25.1 | 6000 | 2.3507 | 19.94 | 6.31 | 19.61 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
