---
library_name: transformers
license: other
base_model: google/medsiglip-448
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: medsiglip-448-ft-crc100k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# medsiglip-448-ft-crc100k

This model is a fine-tuned version of [google/medsiglip-448](https://huggingface.co/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