|
--- |
|
license: apache-2.0 |
|
base_model: facebook/convnextv2-base-22k-384 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: convnext-base-3e-5-weight-decay-2e-8 |
|
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: 0.9373015873015873 |
|
--- |
|
|
|
<!-- 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-3e-5-weight-decay-2e-8 |
|
|
|
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: 0.2472 |
|
- Accuracy: 0.9373 |
|
|
|
## 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.4785 | 1.0 | 1099 | 0.3694 | 0.8871 | |
|
| 0.3622 | 2.0 | 2198 | 0.3020 | 0.9185 | |
|
| 0.2714 | 3.0 | 3297 | 0.2678 | 0.9292 | |
|
| 0.2277 | 4.0 | 4396 | 0.2377 | 0.9392 | |
|
| 0.2028 | 5.0 | 5495 | 0.2595 | 0.9392 | |
|
| 0.1738 | 6.0 | 6594 | 0.2484 | 0.9412 | |
|
| 0.1651 | 7.0 | 7693 | 0.2631 | 0.9400 | |
|
| 0.1155 | 8.0 | 8792 | 0.2552 | 0.9487 | |
|
| 0.1141 | 9.0 | 9891 | 0.2546 | 0.9487 | |
|
| 0.0903 | 10.0 | 10990 | 0.2555 | 0.9479 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
