---
library_name: transformers
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: deft-glitter-211
  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. -->

# deft-glitter-211

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3537
- Accuracy: 0.3164
- Precision: 0.4989
- Recall: 0.3164
- F1: 0.3690
- Roc Auc: 0.6235

## 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: 0.0001
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.4081        | 1.0   | 17   | 1.3928          | 0.2435   | 0.4923    | 0.2435 | 0.3213 | 0.5510  |
| 1.3773        | 2.0   | 34   | 1.3727          | 0.2682   | 0.4966    | 0.2682 | 0.3358 | 0.5862  |
| 1.3568        | 3.0   | 51   | 1.3597          | 0.3008   | 0.4996    | 0.3008 | 0.3587 | 0.6121  |
| 1.3458        | 4.0   | 68   | 1.3544          | 0.3151   | 0.4995    | 0.3151 | 0.3677 | 0.6220  |
| 1.3409        | 5.0   | 85   | 1.3537          | 0.3164   | 0.4989    | 0.3164 | 0.3690 | 0.6235  |


### Framework versions

- Transformers 4.52.3
- Pytorch 2.7.0+cpu
- Datasets 3.6.0
- Tokenizers 0.21.0