---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: convnextv2-base-22k-224-finetuned-tekno24
  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-base-22k-224-finetuned-tekno24

This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9781
- Accuracy: 0.5748
- F1: 0.5697
- Precision: 0.5822
- Recall: 0.5748

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.2643        | 0.9951  | 102  | 1.1487          | 0.5207   | 0.4764 | 0.4783    | 0.5207 |
| 1.1889        | 2.0     | 205  | 1.1038          | 0.5087   | 0.5191 | 0.5565    | 0.5087 |
| 1.215         | 2.9951  | 307  | 1.0810          | 0.4830   | 0.4795 | 0.5589    | 0.4830 |
| 1.1062        | 4.0     | 410  | 1.0103          | 0.5620   | 0.5281 | 0.5358    | 0.5620 |
| 1.089         | 4.9951  | 512  | 1.0459          | 0.5344   | 0.5440 | 0.5720    | 0.5344 |
| 1.0335        | 6.0     | 615  | 0.9781          | 0.5748   | 0.5697 | 0.5822    | 0.5748 |
| 1.0139        | 6.9951  | 717  | 0.9905          | 0.5592   | 0.5605 | 0.5625    | 0.5592 |
| 0.9047        | 8.0     | 820  | 0.9877          | 0.5629   | 0.5525 | 0.5482    | 0.5629 |
| 0.8856        | 8.9951  | 922  | 1.0060          | 0.5565   | 0.5569 | 0.5593    | 0.5565 |
| 0.8306        | 10.0    | 1025 | 0.9907          | 0.5666   | 0.5574 | 0.5531    | 0.5666 |
| 0.8458        | 10.9951 | 1127 | 1.0135          | 0.5500   | 0.5489 | 0.5506    | 0.5500 |
| 0.815         | 11.9415 | 1224 | 1.0185          | 0.5491   | 0.5520 | 0.5558    | 0.5491 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1