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# vit-base-patch16-384-finetuned-ind-5-balanced-1000

This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.2418
- Recall: 0.2418
- F1: 0.0941
- Precision: 0.0584

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0           | 0.97  | 22   | nan             | 0.2418   | 0.2418 | 0.0941 | 0.0584    |
| 0.0           | 1.98  | 45   | nan             | 0.2418   | 0.2418 | 0.0941 | 0.0584    |
| 0.0           | 2.99  | 68   | nan             | 0.2418   | 0.2418 | 0.0941 | 0.0584    |
| 0.0           | 3.87  | 88   | nan             | 0.2418   | 0.2418 | 0.0941 | 0.0584    |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "recall", "f1", "precision"], "base_model": "google/vit-base-patch16-384", "model-index": [{"name": "vit-base-patch16-384-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": 0.24175824175824176, "name": "Accuracy"}, {"type": "recall", "value": 0.24175824175824176, "name": "Recall"}, {"type": "f1", "value": 0.09413595254303218, "name": "F1"}, {"type": "precision", "value": 0.058447047458036465, "name": "Precision"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:google/vit-base-patch16-384 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us