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---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cconvnext-tiny-15ep-1e-4
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: 0.9375
---
<!-- 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. -->
# cconvnext-tiny-15ep-1e-4
This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2767
- Accuracy: 0.9375
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5838 | 1.0 | 550 | 0.4097 | 0.8811 |
| 0.4565 | 2.0 | 1100 | 0.4269 | 0.8763 |
| 0.3628 | 3.0 | 1650 | 0.3464 | 0.9002 |
| 0.2915 | 4.0 | 2200 | 0.3366 | 0.9066 |
| 0.2655 | 5.0 | 2750 | 0.3387 | 0.9054 |
| 0.2395 | 6.0 | 3300 | 0.3313 | 0.9125 |
| 0.2065 | 7.0 | 3850 | 0.3120 | 0.9181 |
| 0.1503 | 8.0 | 4400 | 0.3065 | 0.9221 |
| 0.1503 | 9.0 | 4950 | 0.2948 | 0.9276 |
| 0.1125 | 10.0 | 5500 | 0.2918 | 0.9304 |
| 0.1057 | 11.0 | 6050 | 0.2954 | 0.9328 |
| 0.0937 | 12.0 | 6600 | 0.2959 | 0.9336 |
| 0.0966 | 13.0 | 7150 | 0.2940 | 0.9352 |
| 0.0735 | 14.0 | 7700 | 0.2916 | 0.9340 |
| 0.0881 | 15.0 | 8250 | 0.2902 | 0.9356 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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