---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-resnet50_fashion
  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: 0.8163265306122449
---

<!-- 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-resnet50_fashion

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7982
- Accuracy: 0.8163

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6396        | 0.99  | 86   | 0.7625          | 0.7347   |
| 0.5646        | 2.0   | 173  | 0.5781          | 0.8349   |
| 0.4768        | 2.99  | 259  | 0.4791          | 0.8571   |
| 0.4161        | 4.0   | 346  | 0.3866          | 0.8905   |
| 0.402         | 4.99  | 432  | 0.3294          | 0.9035   |
| 0.369         | 6.0   | 519  | 1.0405          | 0.8924   |
| 0.3512        | 7.0   | 606  | 1.4847          | 0.8905   |
| 0.3439        | 7.99  | 692  | 0.2820          | 0.9054   |
| 0.3306        | 9.0   | 779  | 0.3022          | 0.8850   |
| 0.3691        | 9.93  | 860  | 0.7982          | 0.8163   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3