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# convnext-small-224-leicester_binary

This model is a fine-tuned version of [facebook/convnext-small-224](https://huggingface.co/facebook/convnext-small-224) on the davanstrien/leicester_loaded_annotations_binary dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1283
- F1: 0.9620

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 7    | 0.5143          | 0.8608 |
| 0.5872        | 2.0   | 14   | 0.4215          | 0.8608 |
| 0.3903        | 3.0   | 21   | 0.4127          | 0.8608 |
| 0.3903        | 4.0   | 28   | 0.3605          | 0.8608 |
| 0.3163        | 5.0   | 35   | 0.3152          | 0.8608 |
| 0.2942        | 6.0   | 42   | 0.2942          | 0.8608 |
| 0.2942        | 7.0   | 49   | 0.2669          | 0.8608 |
| 0.2755        | 8.0   | 56   | 0.2316          | 0.8608 |
| 0.2281        | 9.0   | 63   | 0.2104          | 0.8608 |
| 0.2076        | 10.0  | 70   | 0.1938          | 0.8608 |
| 0.2076        | 11.0  | 77   | 0.1803          | 0.8608 |
| 0.1832        | 12.0  | 84   | 0.1704          | 0.8608 |
| 0.1758        | 13.0  | 91   | 0.1650          | 0.8608 |
| 0.1758        | 14.0  | 98   | 0.1714          | 0.8608 |
| 0.167         | 15.0  | 105  | 0.1575          | 0.8608 |
| 0.1519        | 16.0  | 112  | 0.1549          | 0.8608 |
| 0.1519        | 17.0  | 119  | 0.1705          | 0.8608 |
| 0.1422        | 18.0  | 126  | 0.1478          | 0.8608 |
| 0.1444        | 19.0  | 133  | 0.1437          | 0.8608 |
| 0.1396        | 20.0  | 140  | 0.1398          | 0.8608 |
| 0.1396        | 21.0  | 147  | 0.1351          | 0.8608 |
| 0.1293        | 22.0  | 154  | 0.1370          | 0.8987 |
| 0.1361        | 23.0  | 161  | 0.1335          | 0.8987 |
| 0.1361        | 24.0  | 168  | 0.1311          | 0.9367 |
| 0.1246        | 25.0  | 175  | 0.1289          | 0.9620 |
| 0.1211        | 26.0  | 182  | 0.1283          | 0.9620 |
| 0.1211        | 27.0  | 189  | 0.1294          | 0.9620 |
| 0.1182        | 28.0  | 196  | 0.1306          | 0.9620 |
| 0.1172        | 29.0  | 203  | 0.1312          | 0.9620 |
| 0.1102        | 30.0  | 210  | 0.1318          | 0.9620 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2

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