README.md

metadata

license: apache-2.0
base_model: google/efficientnet-b0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: msi-efficientnet-pretrain
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8612813370473538

msi-efficientnet-pretrain

This model is a fine-tuned version of google/efficientnet-b0 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.4941
• Accuracy: 0.8613

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.317	1.0	781	0.9029	0.7535
0.2009	2.0	1562	0.4094	0.8840
0.1405	3.0	2343	0.4941	0.8613

Framework versions

• Transformers 4.36.0
• Pytorch 2.0.1+cu117
• Datasets 2.15.0
• Tokenizers 0.15.0