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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: emotion_classification
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: 0.59375
---
<!-- 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. -->
# emotion_classification
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: 1.1554
- Accuracy: 0.5938
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2477 | 1.0 | 10 | 1.3618 | 0.5625 |
| 1.2002 | 2.0 | 20 | 1.3367 | 0.5625 |
| 1.111 | 3.0 | 30 | 1.3178 | 0.5312 |
| 1.0286 | 4.0 | 40 | 1.2215 | 0.5625 |
| 0.9376 | 5.0 | 50 | 1.2117 | 0.5437 |
| 0.8948 | 6.0 | 60 | 1.2304 | 0.5625 |
| 0.8234 | 7.0 | 70 | 1.1634 | 0.5563 |
| 0.8069 | 8.0 | 80 | 1.2422 | 0.5563 |
| 0.7146 | 9.0 | 90 | 1.2053 | 0.5563 |
| 0.709 | 10.0 | 100 | 1.1887 | 0.575 |
| 0.6404 | 11.0 | 110 | 1.2208 | 0.5563 |
| 0.6301 | 12.0 | 120 | 1.2319 | 0.5687 |
| 0.6107 | 13.0 | 130 | 1.1684 | 0.6 |
| 0.5825 | 14.0 | 140 | 1.1837 | 0.5813 |
| 0.5454 | 15.0 | 150 | 1.1818 | 0.5687 |
| 0.5517 | 16.0 | 160 | 1.1974 | 0.55 |
| 0.4989 | 17.0 | 170 | 1.1304 | 0.6 |
| 0.4875 | 18.0 | 180 | 1.2277 | 0.5375 |
| 0.4881 | 19.0 | 190 | 1.1363 | 0.5875 |
| 0.4951 | 20.0 | 200 | 1.1540 | 0.6062 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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