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# classbird_1

This model is a fine-tuned version of [RobertZ2011/resnet-18-birb](https://huggingface.co/RobertZ2011/resnet-18-birb) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0949
- Accuracy: 0.7726
- Precision: 0.7789
- Recall: 0.7726
- F1: 0.7680

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.5479        | 1.0   | 29   | 2.2789          | 0.2946   | 0.3112    | 0.2946 | 0.2571 |
| 1.9716        | 2.0   | 58   | 1.9112          | 0.4651   | 0.5401    | 0.4651 | 0.4270 |
| 1.506         | 3.0   | 87   | 1.6503          | 0.6202   | 0.6831    | 0.6202 | 0.5933 |
| 1.1838        | 4.0   | 116  | 1.4594          | 0.6667   | 0.6855    | 0.6667 | 0.6439 |
| 0.9704        | 5.0   | 145  | 1.3127          | 0.7183   | 0.7395    | 0.7183 | 0.7064 |
| 0.7997        | 6.0   | 174  | 1.2345          | 0.7468   | 0.7586    | 0.7468 | 0.7410 |
| 0.763         | 7.0   | 203  | 1.1520          | 0.7442   | 0.7493    | 0.7442 | 0.7332 |
| 0.6448        | 8.0   | 232  | 1.1172          | 0.7597   | 0.7745    | 0.7597 | 0.7531 |
| 0.5839        | 9.0   | 261  | 1.0984          | 0.7649   | 0.7753    | 0.7649 | 0.7621 |
| 0.5993        | 10.0  | 290  | 1.0949          | 0.7726   | 0.7789    | 0.7726 | 0.7680 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7 label_8 label_9 label_10 label_11 label_12 label_13 label_14