metadata

license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: resnet-50-finetuned-student_two_classes
    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: 0.85

resnet-50-finetuned-student_two_classes

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: 0.4531
Accuracy: 0.85

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5955	1.0	13	0.4665	0.85
0.5303	2.0	26	0.4790	0.85
0.6127	3.0	39	0.4787	0.85
0.5025	4.0	52	0.4547	0.85
0.471	5.0	65	0.4621	0.85
0.4673	6.0	78	0.4775	0.86
0.4492	7.0	91	0.4648	0.86
0.4144	8.0	104	0.4733	0.85
0.4963	9.0	117	0.4575	0.85
0.4149	10.0	130	0.4691	0.85
0.4588	11.0	143	0.4596	0.84
0.3995	12.0	156	0.4754	0.85
0.359	13.0	169	0.4616	0.85
0.4246	14.0	182	0.4552	0.85
0.4001	15.0	195	0.4839	0.85
0.3919	16.0	208	0.4708	0.85
0.4137	17.0	221	0.4416	0.85
0.3912	18.0	234	0.4507	0.85
0.4322	19.0	247	0.4237	0.85
0.4043	20.0	260	0.4531	0.85

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1