---
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: 0.625798794960745
---

<!-- 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: 0.9830
- Accuracy: 0.6258

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3923        | 0.18  | 1000 | 1.3550          | 0.4712   |
| 1.1517        | 0.37  | 2000 | 1.1854          | 0.5429   |
| 1.2405        | 0.55  | 3000 | 1.1001          | 0.5754   |
| 1.0752        | 0.74  | 4000 | 1.0330          | 0.6018   |
| 1.0986        | 0.92  | 5000 | 0.9973          | 0.6173   |
| 1.0007        | 1.11  | 6000 | 0.9735          | 0.6279   |
| 0.9851        | 1.29  | 7000 | 0.9830          | 0.6258   |


### Framework versions

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