medsiglip-448-ft-crc100k

This model is a fine-tuned version of google/medsiglip-448 on the imagefolder dataset.

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• 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
• lr_scheduler_warmup_steps: 5
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
No log	2.0	24	2.2053

Framework versions

• Transformers 5.5.4
• Pytorch 2.10.0+cu128
• Datasets 4.8.4
• Tokenizers 0.22.2