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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_finetuned_model
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: en-US
split: train
args: en-US
metrics:
- name: Accuracy
type: accuracy
value: 0.5
---
<!-- 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_finetuned_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: 1.3507
- Accuracy: 0.5
## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 20 | 1.6393 | 0.4875 |
| No log | 2.0 | 40 | 1.5461 | 0.4875 |
| No log | 3.0 | 60 | 1.4809 | 0.4938 |
| No log | 4.0 | 80 | 1.4289 | 0.4813 |
| No log | 5.0 | 100 | 1.3878 | 0.4875 |
| No log | 6.0 | 120 | 1.3792 | 0.4813 |
| No log | 7.0 | 140 | 1.3507 | 0.5 |
| No log | 8.0 | 160 | 1.3376 | 0.4938 |
| No log | 9.0 | 180 | 1.3379 | 0.4875 |
| No log | 10.0 | 200 | 1.3305 | 0.5 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|