---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-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. -->

# 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: 0.9429
- Logloss: 0.9429
- Accuracy: {'accuracy': 0.6371511068334937}

## 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 | Logloss | Accuracy                         |
|:-------------:|:------:|:----:|:---------------:|:-------:|:--------------------------------:|
| 1.4538        | 0.9846 | 32   | 1.3816          | 1.3816  | {'accuracy': 0.4475457170356112} |
| 1.2257        | 2.0    | 65   | 1.1411          | 1.1411  | {'accuracy': 0.5668912415784408} |
| 1.0432        | 2.9846 | 97   | 1.0302          | 1.0302  | {'accuracy': 0.6034648700673725} |
| 1.0002        | 4.0    | 130  | 0.9979          | 0.9979  | {'accuracy': 0.615014436958614}  |
| 0.9492        | 4.9846 | 162  | 0.9781          | 0.9781  | {'accuracy': 0.631376323387873}  |
| 0.9302        | 6.0    | 195  | 0.9664          | 0.9664  | {'accuracy': 0.629451395572666}  |
| 0.8805        | 6.9846 | 227  | 0.9515          | 0.9515  | {'accuracy': 0.6371511068334937} |
| 0.852         | 8.0    | 260  | 0.9504          | 0.9504  | {'accuracy': 0.6256015399422522} |
| 0.8352        | 8.9846 | 292  | 0.9468          | 0.9468  | {'accuracy': 0.6371511068334937} |
| 0.8245        | 9.8462 | 320  | 0.9429          | 0.9429  | {'accuracy': 0.6371511068334937} |


### Framework versions

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