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---
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
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