transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- recall
- f1
- precision
model-index:
- name: deit-base-patch16-224-finetuned-ind-14-imbalanced-pan-10847-train
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8703170028818443
    - name: Recall
      type: recall
      value: 0.8703170028818443
    - name: F1
      type: f1
      value: 0.8411548955923809
    - name: Precision
      type: precision
      value: 0.8252839064351536
---

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# deit-base-patch16-224-finetuned-ind-14-imbalanced-pan-10847-train

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4660
- Accuracy: 0.8703
- Recall: 0.8703
- F1: 0.8412
- Precision: 0.8253

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1     | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.7292        | 0.99  | 43   | 0.6759          | 0.7925   | 0.7925 | 0.7582 | 0.7420    |
| 0.5224        | 2.0   | 87   | 0.5146          | 0.8501   | 0.8501 | 0.8228 | 0.8057    |
| 0.5103        | 2.97  | 129  | 0.4916          | 0.8674   | 0.8674 | 0.8391 | 0.8244    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
