my__model
This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. with specialised focus on kneeosteoarthritis data. It achieves the following results on the evaluation set:
- Loss: 1.3439
- Accuracy: 0.4419
Model description
model built to refine the classification with specialised focus on kneeosteoarthritis data. for medical data related to similar domains can use the same to finetune further.
Intended uses & limitations
More information needed
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.3665 | 1.0 | 104 | 1.3439 | 0.4419 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
microsoft/resnet-50