metadata
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-base-5e-5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9376984126984127
convnext-base-5e-5
This model is a fine-tuned version of facebook/convnextv2-base-22k-384 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2535
- Accuracy: 0.9377
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: 5e-05
- train_batch_size: 16
- 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 |
---|---|---|---|---|
0.4987 | 1.0 | 1099 | 0.3869 | 0.8839 |
0.3757 | 2.0 | 2198 | 0.3295 | 0.9026 |
0.2985 | 3.0 | 3297 | 0.3043 | 0.9193 |
0.2535 | 4.0 | 4396 | 0.2558 | 0.9320 |
0.1951 | 5.0 | 5495 | 0.2922 | 0.9316 |
0.1573 | 6.0 | 6594 | 0.2674 | 0.9376 |
0.1432 | 7.0 | 7693 | 0.2857 | 0.9416 |
0.1087 | 8.0 | 8792 | 0.2808 | 0.9447 |
0.1043 | 9.0 | 9891 | 0.2762 | 0.9475 |
0.0757 | 10.0 | 10990 | 0.2755 | 0.9483 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2