---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-FER2013-0.003
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6971301198105322
---

<!-- 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. -->

# resnet-50-finetuned-FER2013-0.003

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9036
- Accuracy: 0.6971

## 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: 0.003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4393        | 1.0   | 224  | 1.2746          | 0.5173   |
| 1.2564        | 2.0   | 448  | 1.1456          | 0.5542   |
| 1.218         | 3.0   | 672  | 1.1102          | 0.5816   |
| 1.1919        | 4.0   | 896  | 1.0255          | 0.6151   |
| 1.1222        | 5.0   | 1120 | 1.0257          | 0.6167   |
| 1.0925        | 6.0   | 1344 | 0.9676          | 0.6317   |
| 1.0241        | 7.0   | 1568 | 0.9406          | 0.6510   |
| 1.0015        | 8.0   | 1792 | 0.9465          | 0.6532   |
| 0.987         | 9.0   | 2016 | 0.9002          | 0.6748   |
| 0.9768        | 10.0  | 2240 | 0.9086          | 0.6737   |
| 0.9408        | 11.0  | 2464 | 0.8975          | 0.6793   |
| 0.8907        | 12.0  | 2688 | 0.8966          | 0.6769   |
| 0.8051        | 13.0  | 2912 | 0.9142          | 0.6826   |
| 0.8169        | 14.0  | 3136 | 0.9082          | 0.6870   |
| 0.7729        | 15.0  | 3360 | 0.9036          | 0.6971   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1