|
--- |
|
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: 0.4875 |
|
--- |
|
|
|
<!-- 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: 1.3327 |
|
- Accuracy: 0.4875 |
|
|
|
## 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: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.8526 | 1.0 | 10 | 1.8929 | 0.3563 | |
|
| 1.7464 | 2.0 | 20 | 1.7105 | 0.3625 | |
|
| 1.6096 | 3.0 | 30 | 1.5898 | 0.4625 | |
|
| 1.4988 | 4.0 | 40 | 1.5056 | 0.5188 | |
|
| 1.4218 | 5.0 | 50 | 1.4349 | 0.4938 | |
|
| 1.3439 | 6.0 | 60 | 1.4127 | 0.525 | |
|
| 1.2799 | 7.0 | 70 | 1.3780 | 0.55 | |
|
| 1.2037 | 8.0 | 80 | 1.3463 | 0.5 | |
|
| 1.1637 | 9.0 | 90 | 1.3236 | 0.55 | |
|
| 1.1361 | 10.0 | 100 | 1.2950 | 0.5437 | |
|
| 1.0836 | 11.0 | 110 | 1.3059 | 0.525 | |
|
| 1.046 | 12.0 | 120 | 1.2707 | 0.525 | |
|
| 1.0277 | 13.0 | 130 | 1.2686 | 0.5563 | |
|
| 1.0236 | 14.0 | 140 | 1.2790 | 0.5062 | |
|
| 0.9926 | 15.0 | 150 | 1.2763 | 0.5687 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.1 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
