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---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-base-15ep
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: 0.9448412698412698
---
<!-- 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. -->
# convnext-base-15ep
This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2376
- Accuracy: 0.9448
## 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: 3e-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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6099 | 1.0 | 1099 | 0.3668 | 0.8934 |
| 0.5086 | 2.0 | 2198 | 0.2773 | 0.9276 |
| 0.386 | 3.0 | 3297 | 0.2587 | 0.9324 |
| 0.335 | 4.0 | 4396 | 0.2400 | 0.9348 |
| 0.3167 | 5.0 | 5495 | 0.2599 | 0.9340 |
| 0.2703 | 6.0 | 6594 | 0.2440 | 0.9419 |
| 0.2638 | 7.0 | 7693 | 0.2496 | 0.9408 |
| 0.1938 | 8.0 | 8792 | 0.2366 | 0.9431 |
| 0.1789 | 9.0 | 9891 | 0.2353 | 0.9487 |
| 0.1738 | 10.0 | 10990 | 0.2380 | 0.9499 |
| 0.1924 | 11.0 | 12089 | 0.2458 | 0.9463 |
| 0.1628 | 12.0 | 13188 | 0.2434 | 0.9491 |
| 0.1431 | 13.0 | 14287 | 0.2390 | 0.9499 |
| 0.1432 | 14.0 | 15386 | 0.2391 | 0.9503 |
| 0.1297 | 15.0 | 16485 | 0.2384 | 0.9499 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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