metadata
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-crop-neck-style
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: 0.8127853881278538
- name: Precision
type: precision
value: 0.8388735739429154
convnextv2-tiny-1k-224-finetuned-crop-neck-style
This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7591
- Accuracy: 0.8128
- Precision: 0.8389
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 | 88 | 0.7865 | 0.7717 | 0.8100 |
| No log | 2.0 | 176 | 0.7591 | 0.8128 | 0.8389 |
| No log | 3.0 | 264 | 0.8601 | 0.7854 | 0.8206 |
| No log | 4.0 | 352 | 0.8518 | 0.8082 | 0.8454 |
| No log | 5.0 | 440 | 0.7959 | 0.8128 | 0.8295 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1