metadata
license: apache-2.0
base_model: dennisjooo/emotion_classification
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: 0.7575
emotion_classification
This model is a fine-tuned version of dennisjooo/emotion_classification on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7891
- Accuracy: 0.7575
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7123 | 1.0 | 25 | 0.8681 | 0.735 |
| 0.6349 | 2.0 | 50 | 0.8721 | 0.73 |
| 0.6354 | 3.0 | 75 | 0.8732 | 0.725 |
| 0.6189 | 4.0 | 100 | 0.8406 | 0.735 |
| 0.6364 | 5.0 | 125 | 0.8456 | 0.74 |
| 0.5833 | 6.0 | 150 | 0.8503 | 0.725 |
| 0.5384 | 7.0 | 175 | 0.8023 | 0.755 |
| 0.5297 | 8.0 | 200 | 0.8002 | 0.7525 |
| 0.5487 | 9.0 | 225 | 0.8253 | 0.745 |
| 0.5068 | 10.0 | 250 | 0.7891 | 0.7575 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1