
<!-- 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. -->

# convnext-tiny-224-finetuned

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9272
- Accuracy: 0.6275
- Precision: 0.6426
- Recall: 0.6275
- F1: 0.6068

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.281         | 0.9846 | 32   | 1.2165          | 0.5428   | 0.5230    | 0.5428 | 0.4989 |
| 1.0964        | 2.0    | 65   | 1.0549          | 0.5823   | 0.5459    | 0.5823 | 0.5427 |
| 0.9929        | 2.9846 | 97   | 0.9905          | 0.6169   | 0.5755    | 0.6169 | 0.5848 |
| 0.9804        | 4.0    | 130  | 0.9691          | 0.6131   | 0.5734    | 0.6131 | 0.5867 |
| 0.9389        | 4.9846 | 162  | 0.9539          | 0.6246   | 0.5874    | 0.6246 | 0.6007 |
| 0.9078        | 6.0    | 195  | 0.9536          | 0.6189   | 0.5910    | 0.6189 | 0.5973 |
| 0.8741        | 6.9846 | 227  | 0.9333          | 0.6333   | 0.5947    | 0.6333 | 0.6098 |
| 0.8523        | 8.0    | 260  | 0.9322          | 0.6323   | 0.5952    | 0.6323 | 0.6122 |
| 0.8222        | 8.9846 | 292  | 0.9354          | 0.6198   | 0.6361    | 0.6198 | 0.5992 |
| 0.7975        | 9.8462 | 320  | 0.9272          | 0.6275   | 0.6426    | 0.6275 | 0.6068 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1

g wd dr nd other