---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: devout-voice-234
  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. -->

# devout-voice-234

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4823
- Accuracy: 0.6195
- Precision: 0.7580
- Recall: 0.6195
- F1: 0.6418
- Roc Auc: 0.9108

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.3843        | 1.0   | 15   | 1.3708          | 0.2922   | 0.5011    | 0.2922 | 0.2957 | 0.6501  |
| 1.3354        | 2.0   | 30   | 1.3256          | 0.5062   | 0.5231    | 0.5062 | 0.4827 | 0.7450  |
| 1.2134        | 3.0   | 45   | 1.1394          | 0.5508   | 0.5749    | 0.5508 | 0.4751 | 0.7934  |
| 1.0408        | 4.0   | 60   | 0.9792          | 0.5188   | 0.6137    | 0.5188 | 0.5357 | 0.8100  |
| 0.881         | 5.0   | 75   | 0.6658          | 0.5508   | 0.5913    | 0.5508 | 0.5508 | 0.8320  |
| 0.7118        | 6.0   | 90   | 0.6165          | 0.5086   | 0.6760    | 0.5086 | 0.5172 | 0.8318  |
| 0.7556        | 7.0   | 105  | 0.5697          | 0.6070   | 0.6564    | 0.6070 | 0.6078 | 0.8671  |
| 0.6212        | 8.0   | 120  | 0.5433          | 0.5664   | 0.7000    | 0.5664 | 0.5755 | 0.8680  |
| 0.5591        | 9.0   | 135  | 0.4504          | 0.6797   | 0.7197    | 0.6797 | 0.6849 | 0.8983  |
| 0.4785        | 10.0  | 150  | 0.4269          | 0.6727   | 0.7115    | 0.6727 | 0.6706 | 0.9120  |
| 0.4093        | 11.0  | 165  | 0.4239          | 0.6742   | 0.7948    | 0.6742 | 0.6650 | 0.9345  |
| 0.4033        | 12.0  | 180  | 0.4823          | 0.6195   | 0.7580    | 0.6195 | 0.6418 | 0.9108  |


### Framework versions

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