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---
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
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