metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: Har_Finetuned-ViT-Hybrid_
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          config: har
          split: train
          args: har
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8984126984126984

Har_Finetuned-ViT-Hybrid_

This model is a fine-tuned version of google/vit-hybrid-base-bit-384 on the image_folder dataset. It achieves the following results on the evaluation set:

Loss: 0.3252
Accuracy: 0.8984

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7647	1.0	167	0.4917	0.8550
0.6376	2.0	334	0.3634	0.8820
0.5051	3.0	501	0.3346	0.8915
0.3472	4.0	668	0.3280	0.8979
0.2982	5.0	835	0.3252	0.8984
0.319	6.0	1002	0.3216	0.8979

Framework versions

Transformers 4.26.1
Pytorch 1.13.0
Datasets 2.1.0
Tokenizers 0.13.2