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. 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