metadata
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
emotion_classification
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.2453
- 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 20 | 1.9465 | 0.325 |
| No log | 2.0 | 40 | 1.7314 | 0.4375 |
| No log | 3.0 | 60 | 1.5249 | 0.5375 |
| No log | 4.0 | 80 | 1.4166 | 0.4875 |
| No log | 5.0 | 100 | 1.3605 | 0.55 |
| No log | 6.0 | 120 | 1.3204 | 0.5563 |
| No log | 7.0 | 140 | 1.2074 | 0.6 |
| No log | 8.0 | 160 | 1.2138 | 0.6 |
| No log | 9.0 | 180 | 1.2600 | 0.5625 |
| No log | 10.0 | 200 | 1.2103 | 0.5563 |
| No log | 11.0 | 220 | 1.1736 | 0.5687 |
| No log | 12.0 | 240 | 1.2462 | 0.5687 |
| No log | 13.0 | 260 | 1.2009 | 0.5813 |
| No log | 14.0 | 280 | 1.2105 | 0.5437 |
| No log | 15.0 | 300 | 1.2705 | 0.5125 |
| No log | 16.0 | 320 | 1.2135 | 0.5938 |
| No log | 17.0 | 340 | 1.2089 | 0.5563 |
| No log | 18.0 | 360 | 1.2818 | 0.5375 |
| No log | 19.0 | 380 | 1.3076 | 0.5062 |
| No log | 20.0 | 400 | 1.2479 | 0.55 |
| No log | 21.0 | 420 | 1.2218 | 0.55 |
| No log | 22.0 | 440 | 1.0957 | 0.6188 |
| No log | 23.0 | 460 | 1.2437 | 0.5875 |
| No log | 24.0 | 480 | 1.3598 | 0.5125 |
| 0.8126 | 25.0 | 500 | 1.2759 | 0.55 |
| 0.8126 | 26.0 | 520 | 1.1474 | 0.6 |
| 0.8126 | 27.0 | 540 | 1.1115 | 0.6375 |
| 0.8126 | 28.0 | 560 | 1.1715 | 0.5687 |
| 0.8126 | 29.0 | 580 | 1.3133 | 0.5625 |
| 0.8126 | 30.0 | 600 | 1.2526 | 0.5437 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1