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convnext-tiny-1e-4

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convnext-tiny-1e-4
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---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-1e-4
  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: 0.9341269841269841
---

<!-- 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-tiny-1e-4

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2564
- Accuracy: 0.9341

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5828        | 1.0   | 550  | 0.4074          | 0.8875   |
| 0.4404        | 2.0   | 1100 | 0.4093          | 0.8811   |
| 0.3503        | 3.0   | 1650 | 0.3391          | 0.9018   |
| 0.2636        | 4.0   | 2200 | 0.3079          | 0.9161   |
| 0.2217        | 5.0   | 2750 | 0.3068          | 0.9169   |
| 0.2024        | 6.0   | 3300 | 0.2839          | 0.9284   |
| 0.1565        | 7.0   | 3850 | 0.2781          | 0.9324   |
| 0.1203        | 8.0   | 4400 | 0.2708          | 0.9388   |
| 0.1281        | 9.0   | 4950 | 0.2707          | 0.9364   |
| 0.1014        | 10.0  | 5500 | 0.2693          | 0.9380   |


### Framework versions

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