Shijia's picture
End of training
ad430ab
|
raw
history blame
2.38 kB
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