---
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: 1.1657
- Logloss: 1.1657
- Accuracy: {'accuracy': 0.5808823529411765}

## 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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Logloss | Accuracy                          |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:---------------------------------:|
| No log        | 0.9412  | 8    | 1.6072          | 1.6072  | {'accuracy': 0.18382352941176472} |
| 1.6101        | 2.0     | 17   | 1.5668          | 1.5668  | {'accuracy': 0.31985294117647056} |
| 1.5645        | 2.9412  | 25   | 1.5246          | 1.5246  | {'accuracy': 0.33455882352941174} |
| 1.4902        | 4.0     | 34   | 1.4774          | 1.4774  | {'accuracy': 0.4007352941176471}  |
| 1.4243        | 4.9412  | 42   | 1.4283          | 1.4283  | {'accuracy': 0.44485294117647056} |
| 1.3502        | 6.0     | 51   | 1.3747          | 1.3747  | {'accuracy': 0.48161764705882354} |
| 1.3502        | 6.9412  | 59   | 1.3332          | 1.3332  | {'accuracy': 0.48161764705882354} |
| 1.2906        | 8.0     | 68   | 1.2978          | 1.2978  | {'accuracy': 0.5036764705882353}  |
| 1.2371        | 8.9412  | 76   | 1.2702          | 1.2702  | {'accuracy': 0.5147058823529411}  |
| 1.1856        | 10.0    | 85   | 1.2434          | 1.2434  | {'accuracy': 0.5404411764705882}  |
| 1.1506        | 10.9412 | 93   | 1.2300          | 1.2300  | {'accuracy': 0.5477941176470589}  |
| 1.0987        | 12.0    | 102  | 1.2088          | 1.2088  | {'accuracy': 0.5588235294117647}  |
| 1.0758        | 12.9412 | 110  | 1.1949          | 1.1949  | {'accuracy': 0.5514705882352942}  |
| 1.0758        | 14.0    | 119  | 1.1896          | 1.1896  | {'accuracy': 0.5588235294117647}  |
| 1.0483        | 14.9412 | 127  | 1.1773          | 1.1773  | {'accuracy': 0.5698529411764706}  |
| 1.0346        | 16.0    | 136  | 1.1719          | 1.1719  | {'accuracy': 0.5735294117647058}  |
| 1.0215        | 16.9412 | 144  | 1.1702          | 1.1702  | {'accuracy': 0.5698529411764706}  |
| 1.0177        | 18.0    | 153  | 1.1666          | 1.1666  | {'accuracy': 0.5772058823529411}  |
| 0.9956        | 18.8235 | 160  | 1.1657          | 1.1657  | {'accuracy': 0.5808823529411765}  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1