---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-MSC-ARMD
  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-base-patch16-224-MSC-ARMD

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: 0.5850
- Accuracy: 0.9

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 14

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.67  | 1    | 1.4427          | 0.25     |
| No log        | 2.0   | 3    | 1.1572          | 0.65     |
| No log        | 2.67  | 4    | 1.0862          | 0.65     |
| No log        | 4.0   | 6    | 0.8420          | 0.85     |
| No log        | 4.67  | 7    | 0.7760          | 0.85     |
| No log        | 6.0   | 9    | 0.6919          | 0.75     |
| 1.0431        | 6.67  | 10   | 0.6586          | 0.8      |
| 1.0431        | 8.0   | 12   | 0.5991          | 0.85     |
| 1.0431        | 8.67  | 13   | 0.5850          | 0.9      |
| 1.0431        | 9.33  | 14   | 0.5747          | 0.9      |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3