metadata
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-nano
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: vuongnhathien/30VNFoods
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9115079365079365
convnext-nano
This model is a fine-tuned version of facebook/convnextv2-nano-22k-384 on the vuongnhathien/30VNFoods dataset. It achieves the following results on the evaluation set:
- Loss: 0.4288
- Accuracy: 0.9115
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: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6173 | 1.0 | 275 | 0.5020 | 0.8473 |
0.3079 | 2.0 | 550 | 0.4532 | 0.8672 |
0.174 | 3.0 | 825 | 0.4498 | 0.8771 |
0.0955 | 4.0 | 1100 | 0.4480 | 0.8907 |
0.0435 | 5.0 | 1375 | 0.4689 | 0.8938 |
0.0282 | 6.0 | 1650 | 0.4556 | 0.9002 |
0.0085 | 7.0 | 1925 | 0.3986 | 0.9161 |
0.0065 | 8.0 | 2200 | 0.4051 | 0.9189 |
0.0012 | 9.0 | 2475 | 0.4022 | 0.9221 |
0.0023 | 10.0 | 2750 | 0.4029 | 0.9217 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2