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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- clothes-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-clothes-classification
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. -->
# vit-clothes-classification
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the DBQ/Matches.Fashion.Product.prices.France dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2328
- Accuracy: 0.6395
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0975 | 0.5714 | 500 | 1.2619 | 0.6111 |
| 0.8315 | 1.1429 | 1000 | 1.3133 | 0.6322 |
| 0.7266 | 1.7143 | 1500 | 1.2077 | 0.6356 |
| 0.5451 | 2.2857 | 2000 | 1.2895 | 0.6556 |
| 0.4287 | 2.8571 | 2500 | 1.2736 | 0.6644 |
| 0.2554 | 3.4286 | 3000 | 1.3801 | 0.6767 |
| 0.2265 | 4.0 | 3500 | 1.4924 | 0.6656 |
| 0.0738 | 4.5714 | 4000 | 1.6321 | 0.68 |
| 0.0761 | 5.1429 | 4500 | 1.6676 | 0.6767 |
| 0.0251 | 5.7143 | 5000 | 1.6911 | 0.7056 |
| 0.0147 | 6.2857 | 5500 | 1.7312 | 0.7 |
| 0.0051 | 6.8571 | 6000 | 1.7282 | 0.6922 |
| 0.0028 | 7.4286 | 6500 | 1.7679 | 0.6967 |
| 0.0017 | 8.0 | 7000 | 1.7642 | 0.6989 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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