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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: 0.55625
---
<!-- 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: 1.3006
- Accuracy: 0.5563
## 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: 0.0001
- train_batch_size: 30
- eval_batch_size: 30
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 22 | 1.8368 | 0.425 |
| No log | 2.0 | 44 | 1.6260 | 0.375 |
| No log | 3.0 | 66 | 1.4368 | 0.5 |
| No log | 4.0 | 88 | 1.3790 | 0.5062 |
| No log | 5.0 | 110 | 1.3382 | 0.5125 |
| No log | 6.0 | 132 | 1.3136 | 0.4938 |
| No log | 7.0 | 154 | 1.2557 | 0.4938 |
| No log | 8.0 | 176 | 1.2959 | 0.5 |
| No log | 9.0 | 198 | 1.2810 | 0.5125 |
| No log | 10.0 | 220 | 1.2689 | 0.5563 |
| No log | 11.0 | 242 | 1.3548 | 0.4875 |
| No log | 12.0 | 264 | 1.2026 | 0.5563 |
| No log | 13.0 | 286 | 1.2096 | 0.575 |
| No log | 14.0 | 308 | 1.3175 | 0.525 |
| No log | 15.0 | 330 | 1.3121 | 0.5312 |
| No log | 16.0 | 352 | 1.4260 | 0.5312 |
| No log | 17.0 | 374 | 1.4547 | 0.5062 |
| No log | 18.0 | 396 | 1.3529 | 0.525 |
| No log | 19.0 | 418 | 1.2386 | 0.5938 |
| No log | 20.0 | 440 | 1.3504 | 0.5375 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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