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mt5-small-text-sum-3
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: 2.3392
- Rouge1: 21.71
- Rouge2: 6.65
- Rougel: 21.31
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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|---|---|---|---|---|---|---|
| 4.6563 | 1.61 | 500 | 2.5975 | 16.78 | 5.15 | 16.64 |
| 3.1112 | 3.22 | 1000 | 2.4856 | 17.05 | 5.31 | 16.8 |
| 2.876 | 4.82 | 1500 | 2.4217 | 18.1 | 5.36 | 17.85 |
| 2.7557 | 6.43 | 2000 | 2.4423 | 18.65 | 5.76 | 18.27 |
| 2.6327 | 8.04 | 2500 | 2.4024 | 19.44 | 6.02 | 19.16 |
| 2.5444 | 9.65 | 3000 | 2.3581 | 18.76 | 5.58 | 18.4 |
| 2.4373 | 11.25 | 3500 | 2.3654 | 19.87 | 6.48 | 19.43 |
| 2.4058 | 12.86 | 4000 | 2.3767 | 19.87 | 5.96 | 19.43 |
| 2.3404 | 14.47 | 4500 | 2.3602 | 20.01 | 5.94 | 19.64 |
| 2.2882 | 16.08 | 5000 | 2.3392 | 21.71 | 6.65 | 21.31 |
| 2.2263 | 17.68 | 5500 | 2.3520 | 20.31 | 6.3 | 20.04 |
| 2.1948 | 19.29 | 6000 | 2.3699 | 21.2 | 6.84 | 20.81 |
| 2.154 | 20.9 | 6500 | 2.3472 | 20.39 | 5.82 | 19.94 |
| 2.1218 | 22.51 | 7000 | 2.3679 | 20.07 | 6.38 | 19.69 |
| 2.073 | 24.12 | 7500 | 2.3457 | 19.7 | 5.8 | 19.2 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
