---
license: apache-2.0
base_model: NekoFi/portrait_cosu_exp4
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: portrait_cosu_exp5
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9583333333333334
    - name: Precision
      type: precision
      value: 0.9581730769230768
    - name: Recall
      type: recall
      value: 0.9583333333333334
    - name: F1
      type: f1
      value: 0.9580274686242009
---

<!-- 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. -->

# portrait_cosu_exp5

This model is a fine-tuned version of [NekoFi/portrait_cosu_exp4](https://huggingface.co/NekoFi/portrait_cosu_exp4) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1603
- Accuracy: 0.9583
- Precision: 0.9582
- Recall: 0.9583
- F1: 0.9580
- Confusion Matrix: [[50, 1], [2, 19]]

## 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: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Confusion Matrix    |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------------------:|
| 0.3966        | 0.9756 | 10   | 0.3024          | 0.8611   | 0.8695    | 0.8611 | 0.8498 | [[50, 1], [9, 12]]  |
| 0.3486        | 1.9512 | 20   | 0.3286          | 0.8333   | 0.8458    | 0.8333 | 0.8147 | [[50, 1], [11, 10]] |
| 0.2347        | 2.9268 | 30   | 0.1769          | 0.9444   | 0.9446    | 0.9444 | 0.9436 | [[50, 1], [3, 18]]  |
| 0.2039        | 3.9024 | 40   | 0.1603          | 0.9583   | 0.9582    | 0.9583 | 0.9580 | [[50, 1], [2, 19]]  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1