---
library_name: transformers
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: 0.9120
- Accuracy: 0.6138
- F1: 0.5996
- Precision: 0.5969
- Recall: 0.6138

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3179        | 0.9968  | 78   | 1.2415          | 0.4207   | 0.3979 | 0.4642    | 0.4207 |
| 1.1998        | 1.9936  | 156  | 1.0769          | 0.5103   | 0.4525 | 0.5309    | 0.5103 |
| 1.168         | 2.9904  | 234  | 1.0573          | 0.5494   | 0.5033 | 0.5605    | 0.5494 |
| 1.1107        | 4.0     | 313  | 0.9924          | 0.5540   | 0.5163 | 0.5257    | 0.5540 |
| 1.1062        | 4.9968  | 391  | 1.0018          | 0.5747   | 0.5507 | 0.5660    | 0.5747 |
| 1.0331        | 5.9936  | 469  | 0.9901          | 0.5931   | 0.5768 | 0.6202    | 0.5931 |
| 1.0409        | 6.9904  | 547  | 0.9634          | 0.5747   | 0.5723 | 0.5722    | 0.5747 |
| 1.0176        | 8.0     | 626  | 0.9504          | 0.5931   | 0.5834 | 0.5814    | 0.5931 |
| 0.995         | 8.9968  | 704  | 0.9584          | 0.5908   | 0.5854 | 0.5853    | 0.5908 |
| 0.9937        | 9.9936  | 782  | 0.9339          | 0.6023   | 0.5934 | 0.5894    | 0.6023 |
| 0.9387        | 10.9904 | 860  | 0.9120          | 0.6138   | 0.5996 | 0.5969    | 0.6138 |
| 0.9324        | 11.9617 | 936  | 0.9135          | 0.5954   | 0.5879 | 0.5865    | 0.5954 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1



![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/w-Uf0Oe9YwVog0rIJxnUw.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/662eb39820de310d1558dd55/_V0cO41hBdBnpBOpcDrWO.png)