metadata
library_name: transformers
license: other
base_model: google/medsiglip-448
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: medsiglip-448-ft-crc100k
results: []
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use 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
Framework versions
- Transformers 4.56.1
- Pytorch 2.3.0+cu121
- Datasets 4.1.1
- Tokenizers 0.22.0