metadata
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-ISIC-dec2024gray
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: 0.916498121930078
resnet-50-finetuned-ISIC-dec2024gray
This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2017
- Accuracy: 0.9165
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 |
|---|---|---|---|---|
| 1.033 | 1.0 | 974 | 0.2387 | 0.9038 |
| 0.9838 | 2.0 | 1948 | 0.2174 | 0.9106 |
| 0.9124 | 3.0 | 2922 | 0.2072 | 0.9148 |
| 0.8492 | 4.0 | 3896 | 0.2037 | 0.9163 |
| 0.9004 | 4.9954 | 4865 | 0.2017 | 0.9165 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.6.0.dev20241225+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0