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convnext-base-3e-5-batch-8

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convnext-base-3e-5-batch-8
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---
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-batch-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: 0.9378968253968254
---

<!-- 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-batch-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: 0.2863
- Accuracy: 0.9379

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5851        | 1.0   | 2198  | 0.3808          | 0.8918   |
| 0.3975        | 2.0   | 4396  | 0.3232          | 0.9093   |
| 0.3337        | 3.0   | 6594  | 0.3210          | 0.9252   |
| 0.2279        | 4.0   | 8792  | 0.3030          | 0.9308   |
| 0.1696        | 5.0   | 10990 | 0.3478          | 0.9292   |
| 0.1658        | 6.0   | 13188 | 0.3084          | 0.9427   |
| 0.1383        | 7.0   | 15386 | 0.3319          | 0.9392   |
| 0.1222        | 8.0   | 17584 | 0.3132          | 0.9479   |
| 0.1196        | 9.0   | 19782 | 0.3136          | 0.9467   |
| 0.1257        | 10.0  | 21980 | 0.3120          | 0.9483   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2