Fine-Tuned-clinical-Summarization
This model is a fine-tuned version of Falconsai/medical_summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1563
- Rouge1: 0.044
- Rouge2: 0.0041
- Rougel: 0.0338
- Rougelsum: 0.0337
- Generated Length: 19.0
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 2 | 5.2591 | 0.044 | 0.0041 | 0.0338 | 0.0337 | 19.0 |
| No log | 2.0 | 4 | 5.1865 | 0.044 | 0.0041 | 0.0338 | 0.0337 | 19.0 |
| No log | 3.0 | 6 | 5.1563 | 0.044 | 0.0041 | 0.0338 | 0.0337 | 19.0 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for Themarina/Fine-Tuned-clinical-Summarization
Base model
Falconsai/medical_summarization