metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swaddling-classifier
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: ahaque/swaddling_classifier
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1
swaddling-classifier
This model is a fine-tuned version of google/vit-base-patch16-224 on the ahaque/swaddling_classifier dataset. It achieves the following results on the evaluation set:
- Loss: 0.4074
- Accuracy: 1.0
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 1 | 0.5106 | 0.6667 |
No log | 2.0 | 2 | 0.4672 | 0.6667 |
No log | 3.0 | 3 | 0.4365 | 1.0 |
No log | 4.0 | 4 | 0.4169 | 1.0 |
No log | 5.0 | 5 | 0.4074 | 1.0 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1