metadata

library_name: transformers
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: mobilenet_v2_1.0_224-finetuned-ISIC-dec2024test
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9276220745449292

mobilenet_v2_1.0_224-finetuned-ISIC-dec2024test

This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.1763
Accuracy: 0.9276

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9055	0.9985	486	0.1955	0.9195
0.8797	1.9985	972	0.2074	0.9138
0.8144	2.9985	1458	0.1797	0.9263
0.9243	3.9985	1944	0.1862	0.9233
0.8199	4.9985	2430	0.1763	0.9276

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cpu
Datasets 3.2.0
Tokenizers 0.21.0