metadata
license: other
base_model: apple/mobilevit-xx-small
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-plankton
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: plankton_fairscope
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8050847457627118
vit-base-plankton
This model is a fine-tuned version of apple/mobilevit-xx-small on the plankton_fairscope dataset. It achieves the following results on the evaluation set:
- Loss: 0.7642
- Accuracy: 0.8051
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: 0.0002
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5476 | 0.52 | 100 | 1.2745 | 0.7419 |
| 1.0997 | 1.04 | 200 | 0.8653 | 0.7842 |
| 0.9498 | 1.56 | 300 | 0.7642 | 0.8051 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0