---
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: aesthetics_v2
  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: 0.5580614847630554
---

<!-- 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. -->

# aesthetics_v2

This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co./facebook/dinov2-large) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6501
- Accuracy: 0.5581

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1465        | 0.17  | 20   | 1.6860          | 0.5313   |
| 1.2703        | 0.34  | 40   | 1.8412          | 0.5014   |
| 1.3152        | 0.52  | 60   | 1.8200          | 0.5042   |
| 1.2313        | 0.69  | 80   | 1.7971          | 0.5112   |
| 1.3476        | 0.86  | 100  | 1.7649          | 0.5100   |
| 1.2597        | 1.03  | 120  | 1.7454          | 0.5175   |
| 1.0094        | 1.2   | 140  | 1.7356          | 0.5257   |
| 0.9743        | 1.37  | 160  | 1.7074          | 0.5352   |
| 1.0209        | 1.55  | 180  | 1.7331          | 0.5322   |
| 1.0692        | 1.72  | 200  | 1.7370          | 0.5331   |
| 1.0556        | 1.89  | 220  | 1.6788          | 0.5487   |
| 0.8634        | 2.06  | 240  | 1.6644          | 0.5536   |
| 0.79          | 2.23  | 260  | 1.6848          | 0.5531   |
| 0.7916        | 2.4   | 280  | 1.6761          | 0.5528   |
| 0.7454        | 2.58  | 300  | 1.6520          | 0.5534   |
| 0.7497        | 2.75  | 320  | 1.6337          | 0.5554   |
| 0.7537        | 2.92  | 340  | 1.6501          | 0.5581   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0
- Datasets 2.17.1
- Tokenizers 0.15.2