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# mobilevit-xx-small-finetuned-ind-5-balanced-1000

This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4820
- Accuracy: 0.6703
- Recall: 0.6703
- F1: 0.6613
- Precision: 0.6657

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | Accuracy | Recall | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 1.6088        | 0.97  | 22   | 1.6075          | 0.6374   | 0.6374 | 0.6147 | 0.6421    |
| 1.6043        | 1.98  | 45   | 1.5946          | 0.6593   | 0.6593 | 0.6453 | 0.6705    |
| 1.5852        | 2.99  | 68   | 1.5484          | 0.6484   | 0.6484 | 0.6299 | 0.6571    |
| 1.5185        | 4.0   | 91   | 1.4788          | 0.6813   | 0.6813 | 0.6688 | 0.6798    |
| 1.4635        | 4.97  | 113  | 1.3974          | 0.6703   | 0.6703 | 0.6528 | 0.6865    |
| 1.3942        | 5.98  | 136  | 1.3194          | 0.6484   | 0.6484 | 0.6196 | 0.6584    |
| 1.3689        | 6.99  | 159  | 1.2598          | 0.6703   | 0.6703 | 0.6425 | 0.6631    |
| 1.3089        | 8.0   | 182  | 1.2088          | 0.6648   | 0.6648 | 0.6464 | 0.6832    |
| 1.2534        | 8.97  | 204  | 1.1869          | 0.6703   | 0.6703 | 0.6607 | 0.7366    |
| 1.2516        | 9.98  | 227  | 1.1685          | 0.6538   | 0.6538 | 0.6392 | 0.7201    |
| 1.2605        | 10.99 | 250  | 1.1220          | 0.6264   | 0.6264 | 0.6003 | 0.6899    |
| 1.2238        | 12.0  | 273  | 1.1493          | 0.5824   | 0.5824 | 0.5671 | 0.6325    |
| 1.2371        | 12.97 | 295  | 1.1598          | 0.5934   | 0.5934 | 0.5757 | 0.7060    |
| 1.2255        | 13.98 | 318  | 1.1449          | 0.6264   | 0.6264 | 0.6085 | 0.6772    |
| 1.1772        | 14.99 | 341  | 1.1199          | 0.6319   | 0.6319 | 0.6224 | 0.6878    |
| 1.1828        | 16.0  | 364  | 1.0684          | 0.6374   | 0.6374 | 0.6332 | 0.6777    |
| 1.1553        | 16.97 | 386  | 1.0732          | 0.6593   | 0.6593 | 0.6466 | 0.7166    |
| 1.1653        | 17.98 | 409  | 1.0861          | 0.6484   | 0.6484 | 0.6342 | 0.7000    |
| 1.1883        | 18.99 | 432  | 1.0659          | 0.6538   | 0.6538 | 0.6332 | 0.7042    |
| 1.1939        | 19.34 | 440  | 1.0684          | 0.6209   | 0.6209 | 0.5876 | 0.6673    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "other", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "recall", "f1", "precision"], "base_model": "apple/mobilevit-xx-small", "model-index": [{"name": "mobilevit-xx-small-finetuned-ind-5-balanced-1000", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6703296703296703, "name": "Accuracy"}, {"type": "recall", "value": 0.6703296703296703, "name": "Recall"}, {"type": "f1", "value": 0.6613268427394721, "name": "F1"}, {"type": "precision", "value": 0.6656503961155124, "name": "Precision"}]}]}]}
transformers tensorboard safetensors mobilevit image-classification generated_from_trainer dataset:imagefolder base_model:apple/mobilevit-xx-small license:other model-index autotrain_compatible endpoints_compatible region:us