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rsna_intracranial_hemorrhage_detection
DifeiT/rsna_intracranial_hemorrhage_detection
rsna_intracranial_hemorrhage_detection is a image classification model from DifeiT. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Sep 17, 2023
- Updated
- Sep 17, 2023
- SHA
- 79a5c0ab
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
rsna_intracranial_hemorrhage_detection
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4344
- Accuracy: 0.8586
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6034 | 1.0 | 132 | 0.5659 | 0.8315 |
| 0.4903 | 2.0 | 265 | 0.4868 | 0.8472 |
| 0.5305 | 3.0 | 397 | 0.4742 | 0.8538 |
| 0.5424 | 4.0 | 530 | 0.4650 | 0.8552 |
| 0.4289 | 5.0 | 662 | 0.4508 | 0.8552 |
| 0.4275 | 6.0 | 795 | 0.4394 | 0.8590 |
| 0.4075 | 7.0 | 927 | 0.4767 | 0.8434 |
| 0.3649 | 8.0 | 1060 | 0.4462 | 0.8595 |
| 0.3934 | 9.0 | 1192 | 0.4323 | 0.8605 |
| 0.3436 | 9.96 | 1320 | 0.4344 | 0.8586 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Sep 17, 2023
- Updated
- Sep 17, 2023