transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:google/vit-base-patch16-224-in21k license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: Pokemon-classification-1stGen-DataAug
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.8973152881701102
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Pokemon-classification-1stGen-DataAug

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4623
- F1: 0.8973

## 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: 6.56462271373806e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.525         | 1.0   | 527  | 3.6420          | 0.4635 |
| 2.6921        | 2.0   | 1055 | 2.0075          | 0.6360 |
| 1.4828        | 3.0   | 1582 | 1.2151          | 0.7582 |
| 0.9262        | 4.0   | 2110 | 0.8820          | 0.8297 |
| 0.6285        | 5.0   | 2637 | 0.6866          | 0.8734 |
| 0.4634        | 6.0   | 3165 | 0.5699          | 0.8854 |
| 0.3683        | 7.0   | 3692 | 0.5223          | 0.8913 |
| 0.3268        | 8.0   | 4220 | 0.4702          | 0.8967 |
| 0.2839        | 8.99  | 4743 | 0.4623          | 0.8973 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.2.0.dev20231126+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
