---
library_name: peft
license: other
base_model: unsloth/medgemma-4b-it-unsloth-bnb-4bit
tags:
- base_model:adapter:unsloth/medgemma-4b-it-unsloth-bnb-4bit
- lora
- transformers
- unsloth
datasets:
- imagefolder
pipeline_tag: text-generation
model-index:
- name: derm-ai
  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. -->

# derm-ai

This model is a fine-tuned version of [unsloth/medgemma-4b-it-unsloth-bnb-4bit](https://huggingface.co/unsloth/medgemma-4b-it-unsloth-bnb-4bit) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0633
- eval_runtime: 87.8654
- eval_samples_per_second: 1.138
- eval_steps_per_second: 0.569
- epoch: 0.4048
- step: 110

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
- mixed_precision_training: Native AMP

### Framework versions

- PEFT 0.16.0
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.3.0
- Tokenizers 0.22.1