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---
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
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