---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: convnextv2-base-22k-384-finetuned
  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-384-finetuned

This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3257
- Accuracy: 0.9611
- F1: 0.9510
- Precision: 0.9714
- Recall: 0.9315

## 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: 0.00015
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 2    | 0.5986          | 0.8167   | 0.8092 | 0.7       | 0.9589 |
| No log        | 2.0   | 4    | 0.3945          | 0.9611   | 0.9510 | 0.9714    | 0.9315 |
| No log        | 3.0   | 6    | 0.3257          | 0.9611   | 0.9510 | 0.9714    | 0.9315 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3