---
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: 0.8707
- Accuracy: 0.7505

## 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: 3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2495        | 0.98  | 31   | 0.9186          | 0.7305   |
| 0.2302        | 2.0   | 63   | 0.8839          | 0.7265   |
| 0.1951        | 2.98  | 94   | 0.9035          | 0.7006   |
| 0.1658        | 4.0   | 126  | 1.0236          | 0.6986   |
| 0.1796        | 4.98  | 157  | 0.8573          | 0.7246   |
| 0.1592        | 6.0   | 189  | 0.9642          | 0.7086   |
| 0.1523        | 6.98  | 220  | 0.9553          | 0.7046   |
| 0.1531        | 8.0   | 252  | 0.9164          | 0.7425   |
| 0.2108        | 8.98  | 283  | 0.8650          | 0.7505   |
| 0.2468        | 9.84  | 310  | 0.8707          | 0.7505   |


### Framework versions

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