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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: Chess_Images
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: 0.9
---
<!-- 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. -->
# Chess_Images
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: 0.5284
- 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: 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 2 | 1.0120 | 0.7 |
| No log | 2.0 | 4 | 0.9958 | 0.8 |
| No log | 3.0 | 6 | 0.9576 | 0.8333 |
| No log | 4.0 | 8 | 0.8673 | 0.8333 |
| 0.8292 | 5.0 | 10 | 0.8140 | 0.8667 |
| 0.8292 | 6.0 | 12 | 0.7034 | 0.9 |
| 0.8292 | 7.0 | 14 | 0.7036 | 0.9 |
| 0.8292 | 8.0 | 16 | 0.6949 | 0.9333 |
| 0.8292 | 9.0 | 18 | 0.5620 | 0.9667 |
| 0.6112 | 10.0 | 20 | 0.5829 | 0.9333 |
| 0.6112 | 11.0 | 22 | 0.6530 | 0.9 |
| 0.6112 | 12.0 | 24 | 0.5664 | 0.9333 |
| 0.6112 | 13.0 | 26 | 0.5084 | 1.0 |
| 0.6112 | 14.0 | 28 | 0.6490 | 0.8333 |
| 0.4805 | 15.0 | 30 | 0.4700 | 1.0 |
| 0.4805 | 16.0 | 32 | 0.5473 | 0.9333 |
| 0.4805 | 17.0 | 34 | 0.4928 | 0.9667 |
| 0.4805 | 18.0 | 36 | 0.5023 | 0.9667 |
| 0.4805 | 19.0 | 38 | 0.4885 | 0.9333 |
| 0.4145 | 20.0 | 40 | 0.5284 | 0.9 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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