metadata
library_name: transformers
license: apache-2.0
base_model: dennisjooo/emotion_classification
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_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: 0.6375
image_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: 1.0965
- Accuracy: 0.6375
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1559 | 1.0 | 20 | 1.2425 | 0.5437 |
| 1.1243 | 2.0 | 40 | 1.1168 | 0.6312 |
| 1.0982 | 3.0 | 60 | 1.1411 | 0.6312 |
| 1.1412 | 4.0 | 80 | 1.1407 | 0.6625 |
| 1.1165 | 5.0 | 100 | 1.1910 | 0.6188 |
| 1.0722 | 6.0 | 120 | 1.1595 | 0.6125 |
| 1.1606 | 7.0 | 140 | 1.1311 | 0.6562 |
| 1.0792 | 8.0 | 160 | 1.1579 | 0.5938 |
| 1.0923 | 9.0 | 180 | 1.2815 | 0.5563 |
| 1.1298 | 10.0 | 200 | 1.0916 | 0.675 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1