---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- fair_face
metrics:
- accuracy
model-index:
- name: trained-age
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: fair_face
      type: fair_face
      config: '0.25'
      split: validation
      args: '0.25'
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5164323534781815
---

<!-- 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. -->

# trained-age

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the fair_face dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1340
- Accuracy: 0.5164

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3347        | 0.18  | 1000 | 1.3819          | 0.4296   |
| 1.3071        | 0.37  | 2000 | 1.2799          | 0.4642   |
| 1.297         | 0.55  | 3000 | 1.2503          | 0.4721   |
| 1.3121        | 0.74  | 4000 | 1.1661          | 0.4995   |
| 1.1806        | 0.92  | 5000 | 1.1137          | 0.5240   |
| 1.0839        | 1.11  | 6000 | 1.1340          | 0.5164   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0