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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: pikachu_model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9786286731967943
---
<!-- 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. -->
# pikachu_model
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: 1.1405
- Accuracy: 0.9786
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9745 | 1.0 | 70 | 3.8989 | 0.5574 |
| 3.0708 | 1.99 | 140 | 3.0319 | 0.8415 |
| 2.4196 | 2.99 | 210 | 2.4623 | 0.9225 |
| 1.9768 | 4.0 | 281 | 2.0344 | 0.9492 |
| 1.6809 | 5.0 | 351 | 1.7300 | 0.9715 |
| 1.4707 | 5.99 | 421 | 1.4962 | 0.9742 |
| 1.2854 | 6.99 | 491 | 1.3465 | 0.9724 |
| 1.1553 | 8.0 | 562 | 1.2592 | 0.9742 |
| 1.0859 | 9.0 | 632 | 1.1849 | 0.9724 |
| 1.0657 | 9.96 | 700 | 1.1405 | 0.9786 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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