medsiglip-448-ft-crc100k

This model is a fine-tuned version of google/medsiglip-448 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 2.4684

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
• gradient_accumulation_steps: 8
• total_train_batch_size: 64
• optimizer: Use OptimizerNames.ADAMW_TORCH 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
3.472	0.4012	50	3.0076
2.7675	0.8024	100	2.4937
2.4427	1.2006	150	2.6831
2.5833	1.6018	200	2.4682
2.3741	2.0	250	2.4684

Framework versions

• Transformers 4.53.2
• Pytorch 2.4.1+cu124
• Datasets 4.0.0
• Tokenizers 0.21.2