metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vitmae-large-funnydataset
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.49783549783549785
vitmae-large-funnydataset
This model is a fine-tuned version of facebook/vit-mae-large on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.4978
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0 | 0.55 | 100 | nan | 0.4978 |
| 0.0 | 1.1 | 200 | nan | 0.4978 |
| 0.0 | 1.66 | 300 | nan | 0.4978 |
| 0.0 | 2.21 | 400 | nan | 0.4978 |
| 0.0 | 2.76 | 500 | nan | 0.4978 |
| 0.0 | 3.31 | 600 | nan | 0.4978 |
| 0.0 | 3.87 | 700 | nan | 0.4978 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3