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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: vit-emotion
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: 0.61875
---
<!-- 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. -->
# vit-emotion
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: 1.1858
- Accuracy: 0.6188
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8403 | 1.0 | 40 | 1.7317 | 0.3063 |
| 1.4783 | 2.0 | 80 | 1.5047 | 0.4938 |
| 1.1866 | 3.0 | 120 | 1.3522 | 0.55 |
| 0.8581 | 4.0 | 160 | 1.2084 | 0.575 |
| 0.6056 | 5.0 | 200 | 1.2348 | 0.5375 |
| 0.3745 | 6.0 | 240 | 1.2119 | 0.5625 |
| 0.2129 | 7.0 | 280 | 1.2012 | 0.5437 |
| 0.1547 | 8.0 | 320 | 1.2181 | 0.5875 |
| 0.1216 | 9.0 | 360 | 1.2196 | 0.5875 |
| 0.1023 | 10.0 | 400 | 1.1858 | 0.6188 |
| 0.102 | 11.0 | 440 | 1.2190 | 0.5938 |
| 0.083 | 12.0 | 480 | 1.2149 | 0.6125 |
| 0.0917 | 13.0 | 520 | 1.2600 | 0.5875 |
| 0.0807 | 14.0 | 560 | 1.2367 | 0.6062 |
| 0.0741 | 15.0 | 600 | 1.2382 | 0.6 |
| 0.0721 | 16.0 | 640 | 1.2464 | 0.5875 |
| 0.0678 | 17.0 | 680 | 1.2548 | 0.5938 |
| 0.0752 | 18.0 | 720 | 1.2591 | 0.5875 |
| 0.0657 | 19.0 | 760 | 1.2590 | 0.6062 |
| 0.0643 | 20.0 | 800 | 1.2589 | 0.5938 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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