---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- fair_face
metrics:
- accuracy
model-index:
- name: trained-race
  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: 0.634380135110462
---

<!-- 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-race

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: 0.9495
- Accuracy: 0.6344

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4995        | 0.18  | 1000  | 1.5133          | 0.4135   |
| 1.3103        | 0.37  | 2000  | 1.2797          | 0.5045   |
| 1.2417        | 0.55  | 3000  | 1.1583          | 0.5451   |
| 1.2142        | 0.74  | 4000  | 1.0952          | 0.5780   |
| 1.0633        | 0.92  | 5000  | 1.0508          | 0.5973   |
| 0.9559        | 1.11  | 6000  | 1.0179          | 0.6106   |
| 0.9984        | 1.29  | 7000  | 0.9958          | 0.6179   |
| 0.9843        | 1.48  | 8000  | 0.9780          | 0.6315   |
| 0.8943        | 1.66  | 9000  | 0.9470          | 0.6386   |
| 0.9941        | 1.84  | 10000 | 0.9495          | 0.6344   |


### Framework versions

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