metadata

tags:
  - generated_from_trainer
datasets:
  - preprocessed1024_config
metrics:
  - accuracy
  - f1
model-index:
  - name: convnext-mlo-512-breat_composition-ordinal
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: preprocessed1024_config
          type: preprocessed1024_config
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value:
              accuracy: 0.12185929648241206
          - name: F1
            type: f1
            value:
              f1: 0.05431131019036954

convnext-mlo-512-breat_composition-ordinal

This model is a fine-tuned version of on the preprocessed1024_config dataset. It achieves the following results on the evaluation set:

Loss: 0.0275
Accuracy: {'accuracy': 0.12185929648241206}
F1: {'f1': 0.05431131019036954}

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.0233	1.0	796	0.0269	{'accuracy': 0.042085427135678394}	{'f1': 0.02019288728149488}
0.0202	2.0	1592	0.0250	{'accuracy': 0.09610552763819095}	{'f1': 0.043839541547277934}
0.0183	3.0	2388	0.0248	{'accuracy': 0.07977386934673367}	{'f1': 0.036940081442699245}
0.0163	4.0	3184	0.0259	{'accuracy': 0.17022613065326633}	{'f1': 0.07273215244229736}
0.0144	5.0	3980	0.0258	{'accuracy': 0.146356783919598}	{'f1': 0.06383561643835617}
0.0117	6.0	4776	0.0249	{'accuracy': 0.0992462311557789}	{'f1': 0.045142857142857144}
0.0105	7.0	5572	0.0256	{'accuracy': 0.10238693467336683}	{'f1': 0.04643874643874644}
0.0084	8.0	6368	0.0261	{'accuracy': 0.12185929648241206}	{'f1': 0.05431131019036954}
0.0071	9.0	7164	0.0270	{'accuracy': 0.10238693467336683}	{'f1': 0.04643874643874644}
0.0065	10.0	7960	0.0275	{'accuracy': 0.12185929648241206}	{'f1': 0.05431131019036954}

Framework versions

Transformers 4.20.1
Pytorch 1.12.0
Datasets 2.1.0
Tokenizers 0.12.1