T5-medi
This model is a fine-tuned version of google/flan-t5-small on Medical QA dataset (wesley7137/qa_dataset). It is just for educational purpose and does not provide accurate results. It achieves the following results on the evaluation set:
- Loss: 0.7130
- Rouge1: 0.3189
- Rouge2: 0.2700
- Rougel: 0.3068
- Rougelsum: 0.3149
Model description
This is a fine-tuned T5 model for Question-Answering tasks in Medical Field
Intended uses & limitations
May struggle with creative or subjective content. Requires fine-tuning for different tasks
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
No log | 1.0 | 223 | 0.8782 | 0.3148 | 0.2630 | 0.3010 | 0.3098 |
No log | 2.0 | 446 | 0.7820 | 0.3148 | 0.2650 | 0.3026 | 0.3111 |
1.1386 | 3.0 | 669 | 0.7456 | 0.3170 | 0.2681 | 0.3049 | 0.3131 |
1.1386 | 4.0 | 892 | 0.7259 | 0.3198 | 0.2699 | 0.3072 | 0.3156 |
0.7884 | 5.0 | 1115 | 0.7130 | 0.3189 | 0.2700 | 0.3068 | 0.3149 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
google/flan-t5-small