---
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: 1.0
    - name: F1
      type: f1
      value:
        f1: 1.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# convnext-mlo-512-breat_composition-ordinal

This model is a fine-tuned version of [](https://huggingface.co/) on the preprocessed1024_config dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0250
- Accuracy: {'accuracy': 1.0}
- F1: {'f1': 1.0}

## 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          |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:-----------:|
| 0.0899        | 1.0   | 796  | 0.0727          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0451        | 2.0   | 1592 | 0.0395          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0388        | 3.0   | 2388 | 0.0382          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0298        | 4.0   | 3184 | 0.0310          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0239        | 5.0   | 3980 | 0.0394          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0194        | 6.0   | 4776 | 0.0254          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0178        | 7.0   | 5572 | 0.0248          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0155        | 8.0   | 6368 | 0.0258          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0137        | 9.0   | 7164 | 0.0247          | {'accuracy': 1.0} | {'f1': 1.0} |
| 0.0129        | 10.0  | 7960 | 0.0250          | {'accuracy': 1.0} | {'f1': 1.0} |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1