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t5-small_corrector_15
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3416
- Rouge1: 34.7998
- Rouge2: 9.0842
- Rougel: 27.8188
- Rougelsum: 27.839
- Gen Len: 18.5561
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 4.2274 | 1.0 | 2365 | 2.9386 | 10.1244 | 1.0024 | 9.1029 | 9.1104 | 18.5377 |
| 2.7936 | 2.0 | 4730 | 2.0196 | 17.7168 | 3.0899 | 15.1305 | 15.1353 | 18.8883 |
| 2.2678 | 3.0 | 7095 | 1.7072 | 26.8501 | 5.7804 | 22.0034 | 22.0213 | 18.839 |
| 1.9029 | 4.0 | 9460 | 1.5254 | 32.9484 | 7.8531 | 26.4538 | 26.4749 | 18.502 |
| 1.5936 | 5.0 | 11825 | 1.3416 | 34.7998 | 9.0842 | 27.8188 | 27.839 | 18.5561 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
