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
model-index:
- name: checkpoint-100
  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: 0.8049689440993789
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# checkpoint-100

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: 0.5022
- Accuracy: 0.8050

## 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: 1e-05
- train_batch_size: 20
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2967        | 1.24  | 50   | 0.9589          | 0.5975   |
| 0.721         | 2.48  | 100  | 0.6094          | 0.7528   |
| 0.5443        | 3.73  | 150  | 0.5702          | 0.7702   |
| 0.4597        | 4.97  | 200  | 0.5168          | 0.7938   |
| 0.3985        | 6.21  | 250  | 0.5091          | 0.7925   |
| 0.3407        | 7.45  | 300  | 0.5011          | 0.8      |
| 0.2989        | 8.7   | 350  | 0.5031          | 0.7963   |
| 0.271         | 9.94  | 400  | 0.4951          | 0.8012   |
| 0.2355        | 11.18 | 450  | 0.4973          | 0.8050   |
| 0.2047        | 12.42 | 500  | 0.5011          | 0.8025   |
| 0.1934        | 13.66 | 550  | 0.5018          | 0.8037   |
| 0.1861        | 14.91 | 600  | 0.5022          | 0.8050   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
