metadata
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
ClinicalT5-base-finetuned-biomedical
This model is a fine-tuned version of 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