T5_base_title_v4
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6697
- Rouge1: 0.4305
- Rouge2: 0.2304
- Rougel: 0.3728
- Rougelsum: 0.3729
- Gen Len: 16.6586
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.9653 | 1.0 | 2019 | 1.7927 | 0.4092 | 0.2145 | 0.3528 | 0.3528 | 16.6021 |
1.828 | 2.0 | 4038 | 1.7374 | 0.4148 | 0.217 | 0.3557 | 0.3558 | 16.7601 |
1.7597 | 3.0 | 6057 | 1.7053 | 0.4183 | 0.2199 | 0.3595 | 0.3594 | 16.8878 |
1.6787 | 4.0 | 8076 | 1.6875 | 0.4221 | 0.224 | 0.3649 | 0.3647 | 16.6098 |
1.6361 | 5.0 | 10095 | 1.6730 | 0.4227 | 0.2229 | 0.3655 | 0.3657 | 16.6044 |
1.6032 | 6.0 | 12114 | 1.6679 | 0.4266 | 0.227 | 0.3696 | 0.3697 | 16.4617 |
1.5701 | 7.0 | 14133 | 1.6657 | 0.4265 | 0.2273 | 0.3694 | 0.3692 | 16.4184 |
1.5359 | 8.0 | 16152 | 1.6677 | 0.4273 | 0.2274 | 0.3695 | 0.3695 | 16.5704 |
1.5136 | 9.0 | 18171 | 1.6639 | 0.4271 | 0.2278 | 0.3697 | 0.3697 | 16.5989 |
1.4776 | 10.0 | 20190 | 1.6641 | 0.4291 | 0.2297 | 0.3723 | 0.3722 | 16.5137 |
1.4507 | 11.0 | 22209 | 1.6650 | 0.4307 | 0.2303 | 0.372 | 0.3718 | 16.5868 |
1.437 | 12.0 | 24228 | 1.6654 | 0.4277 | 0.2274 | 0.3711 | 0.3711 | 16.7277 |
1.4428 | 13.0 | 26247 | 1.6689 | 0.4296 | 0.2287 | 0.3714 | 0.3715 | 16.7078 |
1.4183 | 14.0 | 28266 | 1.6697 | 0.4307 | 0.2301 | 0.3726 | 0.3725 | 16.6979 |
1.4244 | 15.0 | 30285 | 1.6697 | 0.4305 | 0.2304 | 0.3728 | 0.3729 | 16.6586 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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Base model
google-t5/t5-base