metadata
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-base-8e-5-15ep
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: 0.9369047619047619
convnext-base-8e-5-15ep
This model is a fine-tuned version of facebook/convnextv2-base-22k-384 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3097
- Accuracy: 0.9369
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: 8e-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 |
|---|---|---|---|---|
| 0.5403 | 1.0 | 1099 | 0.4231 | 0.8744 |
| 0.4376 | 2.0 | 2198 | 0.3817 | 0.8899 |
| 0.3601 | 3.0 | 3297 | 0.3818 | 0.9018 |
| 0.3202 | 4.0 | 4396 | 0.3153 | 0.9201 |
| 0.2463 | 5.0 | 5495 | 0.3216 | 0.9229 |
| 0.2051 | 6.0 | 6594 | 0.3338 | 0.9213 |
| 0.2108 | 7.0 | 7693 | 0.3224 | 0.9272 |
| 0.1568 | 8.0 | 8792 | 0.3127 | 0.9356 |
| 0.1491 | 9.0 | 9891 | 0.3258 | 0.9352 |
| 0.0998 | 10.0 | 10990 | 0.3257 | 0.9348 |
| 0.0728 | 11.0 | 12089 | 0.3289 | 0.9368 |
| 0.0872 | 12.0 | 13188 | 0.3288 | 0.9408 |
| 0.0731 | 13.0 | 14287 | 0.3320 | 0.9408 |
| 0.0693 | 14.0 | 15386 | 0.3270 | 0.9423 |
| 0.0586 | 15.0 | 16485 | 0.3251 | 0.9427 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2