t5_medical_diagnostic_peft
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7468
- Rouge1: 0.4227
- Rouge2: 0.2234
- Rougel: 0.3594
- Rougelsum: 0.3595
- Gen Len: 17.5843
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: 0.001
- 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: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.9974 | 0.2 | 500 | 1.7864 | 0.4167 | 0.221 | 0.3561 | 0.356 | 17.6092 |
1.9244 | 0.4 | 1000 | 1.7504 | 0.4166 | 0.2214 | 0.3577 | 0.3577 | 16.9937 |
1.9121 | 0.6 | 1500 | 1.7274 | 0.4209 | 0.2245 | 0.3593 | 0.3594 | 17.2876 |
1.8677 | 0.8 | 2000 | 1.7101 | 0.4253 | 0.2266 | 0.363 | 0.3631 | 17.5681 |
1.8927 | 1.0 | 2500 | 1.7468 | 0.4227 | 0.2234 | 0.3594 | 0.3595 | 17.5843 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
Model tree for fahmiaziz/t5-medical-diagnosis
Base model
google-t5/t5-base