--- base_model: luqh/ClinicalT5-base tags: - generated_from_trainer datasets: - sem_eval_2024_task_2 metrics: - rouge model-index: - name: ClinicalT5-base-finetuned-biomedical results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: sem_eval_2024_task_2 type: sem_eval_2024_task_2 config: sem_eval_2024_task_2_source split: validation args: sem_eval_2024_task_2_source metrics: - name: Rouge1 type: rouge value: 51.0 --- # ClinicalT5-base-finetuned-biomedical This model is a fine-tuned version of [luqh/ClinicalT5-base](https://huggingface.co/luqh/ClinicalT5-base) on the sem_eval_2024_task_2 dataset. It achieves the following results on the evaluation set: - Loss: 0.2017 - Rouge1: 51.0 - Rouge2: 0.0 - Rougel: 51.0 - Rougelsum: 51.0 - Gen Len: 3.71 ## 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: 4 - eval_batch_size: 4 - 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 | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | No log | 1.0 | 425 | 0.2227 | 49.5 | 0.0 | 49.5 | 49.5 | 3.015 | | 1.7568 | 2.0 | 850 | 0.2053 | 49.0 | 0.0 | 49.0 | 49.0 | 3.09 | | 0.227 | 3.0 | 1275 | 0.2012 | 51.0 | 0.0 | 51.0 | 51.0 | 3.24 | | 0.2186 | 4.0 | 1700 | 0.2011 | 52.0 | 0.0 | 52.0 | 52.0 | 3.29 | | 0.2173 | 5.0 | 2125 | 0.2017 | 51.0 | 0.0 | 51.0 | 51.0 | 3.71 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0