---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-1k-224-finetuned-sleeve-length
  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: 0.8620689655172413
---

<!-- 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-tiny-1k-224-finetuned-sleeve-length

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5496
- Accuracy: 0.8621

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 6    | 1.7957          | 0.2299   |
| 1.8656        | 1.92  | 12   | 1.7704          | 0.2759   |
| 1.8656        | 2.88  | 18   | 1.7382          | 0.3218   |
| 1.7835        | 4.0   | 25   | 1.6674          | 0.3793   |
| 1.664         | 4.96  | 31   | 1.5982          | 0.4253   |
| 1.664         | 5.92  | 37   | 1.4861          | 0.4368   |
| 1.5072        | 6.88  | 43   | 1.3645          | 0.4713   |
| 1.3304        | 8.0   | 50   | 1.2859          | 0.4598   |
| 1.3304        | 8.96  | 56   | 1.2796          | 0.4713   |
| 1.1651        | 9.92  | 62   | 1.2456          | 0.5172   |
| 1.1651        | 10.88 | 68   | 1.1667          | 0.5402   |
| 1.0876        | 12.0  | 75   | 1.1510          | 0.5632   |
| 1.0046        | 12.96 | 81   | 1.0510          | 0.6092   |
| 1.0046        | 13.92 | 87   | 1.0338          | 0.5862   |
| 0.9465        | 14.88 | 93   | 0.9883          | 0.5862   |
| 0.8699        | 16.0  | 100  | 0.9882          | 0.5632   |
| 0.8699        | 16.96 | 106  | 0.9276          | 0.5747   |
| 0.7969        | 17.92 | 112  | 0.9145          | 0.5862   |
| 0.7969        | 18.88 | 118  | 0.8144          | 0.6667   |
| 0.7254        | 20.0  | 125  | 0.7587          | 0.6667   |
| 0.6447        | 20.96 | 131  | 0.6990          | 0.7471   |
| 0.6447        | 21.92 | 137  | 0.7042          | 0.7241   |
| 0.6021        | 22.88 | 143  | 0.6526          | 0.7701   |
| 0.516         | 24.0  | 150  | 0.6485          | 0.8046   |
| 0.516         | 24.96 | 156  | 0.5803          | 0.8161   |
| 0.4497        | 25.92 | 162  | 0.6085          | 0.8046   |
| 0.4497        | 26.88 | 168  | 0.6095          | 0.8046   |
| 0.3935        | 28.0  | 175  | 0.5372          | 0.8276   |
| 0.3321        | 28.96 | 181  | 0.5829          | 0.8161   |
| 0.3321        | 29.92 | 187  | 0.6205          | 0.8161   |
| 0.3007        | 30.88 | 193  | 0.5150          | 0.8276   |
| 0.2618        | 32.0  | 200  | 0.6069          | 0.8391   |
| 0.2618        | 32.96 | 206  | 0.5273          | 0.8391   |
| 0.2411        | 33.92 | 212  | 0.4727          | 0.8621   |
| 0.2411        | 34.88 | 218  | 0.4611          | 0.8736   |
| 0.2108        | 36.0  | 225  | 0.5696          | 0.8506   |
| 0.2143        | 36.96 | 231  | 0.4944          | 0.8621   |
| 0.2143        | 37.92 | 237  | 0.5628          | 0.8161   |
| 0.1663        | 38.88 | 243  | 0.6131          | 0.8046   |
| 0.1714        | 40.0  | 250  | 0.4962          | 0.8506   |
| 0.1714        | 40.96 | 256  | 0.5023          | 0.8391   |
| 0.174         | 41.92 | 262  | 0.4842          | 0.8276   |
| 0.174         | 42.88 | 268  | 0.4679          | 0.8276   |
| 0.138         | 44.0  | 275  | 0.6271          | 0.8161   |
| 0.1437        | 44.96 | 281  | 0.5326          | 0.8506   |
| 0.1437        | 45.92 | 287  | 0.5655          | 0.8161   |
| 0.136         | 46.88 | 293  | 0.4672          | 0.8391   |
| 0.1401        | 48.0  | 300  | 0.4990          | 0.8621   |
| 0.1401        | 48.96 | 306  | 0.5445          | 0.8276   |
| 0.1281        | 49.92 | 312  | 0.4761          | 0.8736   |
| 0.1281        | 50.88 | 318  | 0.5665          | 0.8506   |
| 0.1156        | 52.0  | 325  | 0.5090          | 0.8506   |
| 0.0981        | 52.96 | 331  | 0.5152          | 0.8506   |
| 0.0981        | 53.92 | 337  | 0.5466          | 0.8161   |
| 0.1055        | 54.88 | 343  | 0.5390          | 0.8276   |
| 0.112         | 56.0  | 350  | 0.5574          | 0.8506   |
| 0.112         | 56.96 | 356  | 0.5449          | 0.8506   |
| 0.0855        | 57.92 | 362  | 0.5390          | 0.8506   |
| 0.0855        | 58.88 | 368  | 0.5206          | 0.8506   |
| 0.0899        | 60.0  | 375  | 0.5476          | 0.8621   |
| 0.1026        | 60.96 | 381  | 0.5344          | 0.8506   |
| 0.1026        | 61.92 | 387  | 0.5531          | 0.8391   |
| 0.0799        | 62.88 | 393  | 0.5723          | 0.8276   |
| 0.0844        | 64.0  | 400  | 0.5340          | 0.8161   |
| 0.0844        | 64.96 | 406  | 0.5236          | 0.8736   |
| 0.0724        | 65.92 | 412  | 0.6137          | 0.8391   |
| 0.0724        | 66.88 | 418  | 0.5825          | 0.8276   |
| 0.0867        | 68.0  | 425  | 0.5105          | 0.8621   |
| 0.071         | 68.96 | 431  | 0.5272          | 0.8506   |
| 0.071         | 69.92 | 437  | 0.5524          | 0.8506   |
| 0.0723        | 70.88 | 443  | 0.5508          | 0.8391   |
| 0.0748        | 72.0  | 450  | 0.5689          | 0.8161   |
| 0.0748        | 72.96 | 456  | 0.5556          | 0.8506   |
| 0.0589        | 73.92 | 462  | 0.5452          | 0.8506   |
| 0.0589        | 74.88 | 468  | 0.5475          | 0.8621   |
| 0.0719        | 76.0  | 475  | 0.5484          | 0.8621   |
| 0.0801        | 76.8  | 480  | 0.5496          | 0.8621   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1