metadata
library_name: transformers
language:
- en
license: other
base_model: google/medsiglip-448
tags:
- generated_from_trainer
metrics:
- recall
- precision
- accuracy
model-index:
- name: medsiglip-448
results: []
medsiglip-448
This model is a fine-tuned version of google/medsiglip-448 on the vllm-pneumonia-detection/mimic-cxr-labelled-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2236
- F1-score: 0.7601
- Sensitivity: 0.4673
- Specificity: 0.9754
- Recall: 0.7213
- Precision: 0.8271
- Accuracy: 0.9135
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: 5e-06
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score | Sensitivity | Specificity | Recall | Precision | Accuracy |
|---|---|---|---|---|---|---|---|---|---|
| 0.2792 | 0.4363 | 500 | 0.2565 | 0.733 | 0.4112 | 0.9754 | 0.6933 | 0.8106 | 0.9067 |
| 0.2243 | 0.8726 | 1000 | 0.2367 | 0.7376 | 0.4206 | 0.9754 | 0.698 | 0.8135 | 0.9078 |
| 0.2088 | 1.3089 | 1500 | 0.2167 | 0.7792 | 0.5047 | 0.9767 | 0.7407 | 0.8422 | 0.9192 |
| 0.2079 | 1.7452 | 2000 | 0.2220 | 0.7525 | 0.4112 | 0.9883 | 0.6998 | 0.877 | 0.9181 |
| 0.1989 | 2.1815 | 2500 | 0.2236 | 0.7601 | 0.4673 | 0.9754 | 0.7213 | 0.8271 | 0.9135 |
Framework versions
- Transformers 4.54.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4