---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- catbreed
metrics:
- accuracy
base_model: google/vit-base-patch16-224-in21k
model-index:
- name: catbreed
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: catbreed
      type: catbreed
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.9252136752136753
      name: Accuracy
---

<!-- 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. -->

# catbreed

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 catbreed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7210
- Accuracy: 0.9252

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1329        | 0.99  | 29   | 1.7492          | 0.8376   |
| 1.3437        | 1.98  | 58   | 1.1638          | 0.9038   |
| 0.9266        | 2.97  | 87   | 0.9013          | 0.8974   |
| 0.7274        | 4.0   | 117  | 0.7345          | 0.9338   |
| 0.6652        | 4.96  | 145  | 0.7210          | 0.9252   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3