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---
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-fullwear-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: 0.8229166666666666
- name: Precision
type: precision
value: 0.8355769851835295
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# convnextv2-tiny-1k-224-finetuned-fullwear-v2
This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5128
- Accuracy: 0.8229
- Precision: 0.8356
## 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 | 116 | 1.8085 | 0.5625 | 0.6486 |
| No log | 2.0 | 232 | 1.2627 | 0.6771 | 0.7218 |
| No log | 3.0 | 348 | 1.0071 | 0.6806 | 0.7166 |
| No log | 4.0 | 464 | 0.8603 | 0.7188 | 0.7466 |
| 1.3688 | 5.0 | 580 | 0.7240 | 0.7708 | 0.8074 |
| 1.3688 | 6.0 | 696 | 0.7496 | 0.7535 | 0.7994 |
| 1.3688 | 7.0 | 812 | 0.5832 | 0.8056 | 0.8176 |
| 1.3688 | 8.0 | 928 | 0.5809 | 0.7986 | 0.8156 |
| 0.4904 | 9.0 | 1044 | 0.5456 | 0.7986 | 0.8052 |
| 0.4904 | 10.0 | 1160 | 0.5833 | 0.7951 | 0.8198 |
| 0.4904 | 11.0 | 1276 | 0.5782 | 0.7986 | 0.8069 |
| 0.4904 | 12.0 | 1392 | 0.5128 | 0.8229 | 0.8356 |
| 0.2966 | 13.0 | 1508 | 0.5421 | 0.8160 | 0.8319 |
| 0.2966 | 14.0 | 1624 | 0.6090 | 0.7847 | 0.8171 |
| 0.2966 | 15.0 | 1740 | 0.6090 | 0.8021 | 0.8135 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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