---
license: apache-2.0
base_model: facebook/convnextv2-large-22k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ConvNextV2-large-DogBreed
  results: []
---

<!-- 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. -->

# ConvNextV2-large-DogBreed

This model is a fine-tuned version of [facebook/convnextv2-large-22k-224](https://huggingface.co/facebook/convnextv2-large-22k-224) on dog breed classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5469
- Accuracy: 0.9139

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.8578        | 1.0   | 13   | 4.6940          | 0.0671   |
| 4.6332        | 1.99  | 26   | 4.4169          | 0.1784   |
| 4.4095        | 2.99  | 39   | 4.1105          | 0.3485   |
| 3.8841        | 3.98  | 52   | 3.7581          | 0.5198   |
| 3.5964        | 4.98  | 65   | 3.3647          | 0.6647   |
| 3.2781        | 5.97  | 78   | 2.9442          | 0.7677   |
| 2.6006        | 6.97  | 91   | 2.5252          | 0.8180   |
| 2.2638        | 7.96  | 104  | 2.1256          | 0.8467   |
| 1.9609        | 8.96  | 117  | 1.7626          | 0.8766   |
| 1.3962        | 9.95  | 130  | 1.4453          | 0.9042   |
| 1.143         | 10.95 | 143  | 1.1818          | 0.9102   |
| 0.9423        | 11.94 | 156  | 0.9697          | 0.9138   |
| 0.7674        | 12.94 | 169  | 0.8097          | 0.9174   |
| 0.5007        | 13.93 | 182  | 0.6922          | 0.9186   |
| 0.4097        | 14.93 | 195  | 0.5999          | 0.9162   |
| 0.3392        | 16.0  | 209  | 0.5174          | 0.9269   |
| 0.2285        | 17.0  | 222  | 0.4685          | 0.9257   |
| 0.184         | 17.99 | 235  | 0.4337          | 0.9210   |
| 0.1587        | 18.99 | 248  | 0.4058          | 0.9257   |
| 0.1112        | 19.98 | 261  | 0.3824          | 0.9222   |
| 0.0967        | 20.98 | 274  | 0.3712          | 0.9150   |
| 0.0838        | 21.97 | 287  | 0.3584          | 0.9186   |
| 0.0665        | 22.97 | 300  | 0.3468          | 0.9174   |
| 0.0589        | 23.96 | 313  | 0.3428          | 0.9186   |
| 0.0551        | 24.96 | 326  | 0.3364          | 0.9186   |
| 0.0512        | 25.95 | 339  | 0.3334          | 0.9162   |
| 0.0441        | 26.95 | 352  | 0.3278          | 0.9210   |
| 0.0428        | 27.94 | 365  | 0.3275          | 0.9150   |
| 0.0387        | 28.94 | 378  | 0.3237          | 0.9210   |
| 0.036         | 29.93 | 391  | 0.3242          | 0.9150   |
| 0.0337        | 30.93 | 404  | 0.3204          | 0.9186   |
| 0.0328        | 32.0  | 418  | 0.3176          | 0.9198   |
| 0.0304        | 33.0  | 431  | 0.3183          | 0.9162   |
| 0.0283        | 33.99 | 444  | 0.3150          | 0.9210   |
| 0.029         | 34.99 | 457  | 0.3168          | 0.9174   |
| 0.0264        | 35.98 | 470  | 0.3146          | 0.9174   |
| 0.0259        | 36.98 | 483  | 0.3162          | 0.9174   |
| 0.0258        | 37.97 | 496  | 0.3126          | 0.9186   |
| 0.0251        | 38.97 | 509  | 0.3131          | 0.9174   |
| 0.0239        | 39.96 | 522  | 0.3145          | 0.9186   |
| 0.0234        | 40.96 | 535  | 0.3120          | 0.9198   |
| 0.023         | 41.95 | 548  | 0.3102          | 0.9198   |
| 0.0226        | 42.95 | 561  | 0.3123          | 0.9198   |
| 0.0222        | 43.94 | 574  | 0.3140          | 0.9186   |
| 0.0225        | 44.94 | 587  | 0.3119          | 0.9186   |
| 0.0215        | 45.93 | 600  | 0.3106          | 0.9198   |
| 0.0209        | 46.93 | 613  | 0.3113          | 0.9198   |
| 0.0212        | 48.0  | 627  | 0.3115          | 0.9198   |
| 0.021         | 49.0  | 640  | 0.3113          | 0.9198   |
| 0.0212        | 49.76 | 650  | 0.3113          | 0.9198   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1