transformers safetensors vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: WS800_ViT_42895082
  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. -->

# WS800_ViT_42895082

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0776
- Accuracy: 0.9875

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 0.6859          | 0.925    |
| No log        | 2.0   | 10   | 0.6328          | 0.975    |
| No log        | 3.0   | 15   | 0.5301          | 0.975    |
| No log        | 4.0   | 20   | 0.4404          | 0.9625   |
| No log        | 5.0   | 25   | 0.3480          | 0.975    |
| No log        | 6.0   | 30   | 0.2758          | 0.975    |
| No log        | 7.0   | 35   | 0.2179          | 0.9875   |
| No log        | 8.0   | 40   | 0.1789          | 0.9875   |
| No log        | 9.0   | 45   | 0.1505          | 0.9875   |
| 0.3788        | 10.0  | 50   | 0.1296          | 0.9875   |
| 0.3788        | 11.0  | 55   | 0.1145          | 0.9875   |
| 0.3788        | 12.0  | 60   | 0.1034          | 0.9875   |
| 0.3788        | 13.0  | 65   | 0.0954          | 0.9875   |
| 0.3788        | 14.0  | 70   | 0.0895          | 0.9875   |
| 0.3788        | 15.0  | 75   | 0.0853          | 0.9875   |
| 0.3788        | 16.0  | 80   | 0.0822          | 0.9875   |
| 0.3788        | 17.0  | 85   | 0.0801          | 0.9875   |
| 0.3788        | 18.0  | 90   | 0.0787          | 0.9875   |
| 0.3788        | 19.0  | 95   | 0.0779          | 0.9875   |
| 0.0547        | 20.0  | 100  | 0.0776          | 0.9875   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
