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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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