metadata

license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold1
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8548696844993141

Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold1

This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 1.5790
Accuracy: 0.8549

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3103	1.0	914	0.3588	0.8494
0.3671	2.0	1828	0.3382	0.8669
0.2679	3.0	2742	0.4568	0.8491
0.13	4.0	3656	0.7675	0.8595
0.0539	5.0	4570	1.0063	0.8543
0.0034	6.0	5484	1.3345	0.8543
0.001	7.0	6398	1.4146	0.8562
0.0013	8.0	7312	1.6343	0.8529
0.0023	9.0	8226	1.5956	0.8486
0.0001	10.0	9140	1.5790	0.8549

Framework versions

Transformers 4.32.1
Pytorch 2.0.1
Datasets 2.12.0
Tokenizers 0.13.2