metadata
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- precision
model-index:
- name: convnextv2-tiny-1k-224-finetuned-print-type-v2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9052631578947369
- name: Precision
type: precision
value: 0.9102193842350079
convnextv2-tiny-1k-224-finetuned-print-type-v2
This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3418
- Accuracy: 0.9053
- Precision: 0.9102
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: 2e-05
- train_batch_size: 10
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision |
|---|---|---|---|---|---|
| No log | 1.0 | 76 | 0.8899 | 0.7842 | 0.8005 |
| No log | 2.0 | 152 | 0.5119 | 0.8526 | 0.8568 |
| No log | 3.0 | 228 | 0.3834 | 0.8737 | 0.8773 |
| No log | 4.0 | 304 | 0.3494 | 0.8947 | 0.8973 |
| No log | 5.0 | 380 | 0.3822 | 0.8737 | 0.8859 |
| No log | 6.0 | 456 | 0.3840 | 0.8842 | 0.8985 |
| 0.4844 | 7.0 | 532 | 0.3418 | 0.9053 | 0.9102 |
| 0.4844 | 8.0 | 608 | 0.3430 | 0.9158 | 0.9152 |
| 0.4844 | 9.0 | 684 | 0.4108 | 0.9105 | 0.9135 |
| 0.4844 | 10.0 | 760 | 0.3836 | 0.9211 | 0.9216 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1