---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fashion-clothing-decade
  results: []
---

<!-- 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. -->

# fashion-clothing-decade

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8451
- Accuracy: 0.7485

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9496        | 0.98  | 31   | 1.1401          | 0.6766   |
| 0.7981        | 2.0   | 63   | 1.0490          | 0.6926   |
| 0.6665        | 2.98  | 94   | 1.0096          | 0.6766   |
| 0.5422        | 4.0   | 126  | 0.9923          | 0.6886   |
| 0.4987        | 4.98  | 157  | 0.9207          | 0.7285   |
| 0.447         | 6.0   | 189  | 0.9480          | 0.6866   |
| 0.3892        | 6.98  | 220  | 0.9274          | 0.7026   |
| 0.3632        | 8.0   | 252  | 0.8786          | 0.7445   |
| 0.3886        | 8.98  | 283  | 0.8331          | 0.7645   |
| 0.3778        | 9.84  | 310  | 0.8451          | 0.7485   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1