---
license: apache-2.0
base_model: facebook/deit-base-distilled-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: WS800_DeiT_42895082
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# WS800_DeiT_42895082

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2587
- Accuracy: 0.975

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 0.6389          | 0.5125   |
| No log        | 2.0   | 10   | 0.1840          | 0.9375   |
| No log        | 3.0   | 15   | 0.1272          | 0.9625   |
| No log        | 4.0   | 20   | 0.1958          | 0.9625   |
| No log        | 5.0   | 25   | 0.1635          | 0.975    |
| No log        | 6.0   | 30   | 0.2280          | 0.975    |
| No log        | 7.0   | 35   | 0.2664          | 0.9625   |
| No log        | 8.0   | 40   | 0.2636          | 0.9625   |
| No log        | 9.0   | 45   | 0.2582          | 0.975    |
| 0.1252        | 10.0  | 50   | 0.2571          | 0.975    |
| 0.1252        | 11.0  | 55   | 0.2571          | 0.975    |
| 0.1252        | 12.0  | 60   | 0.2572          | 0.975    |
| 0.1252        | 13.0  | 65   | 0.2574          | 0.975    |
| 0.1252        | 14.0  | 70   | 0.2577          | 0.975    |
| 0.1252        | 15.0  | 75   | 0.2580          | 0.975    |
| 0.1252        | 16.0  | 80   | 0.2582          | 0.975    |
| 0.1252        | 17.0  | 85   | 0.2584          | 0.975    |
| 0.1252        | 18.0  | 90   | 0.2586          | 0.975    |
| 0.1252        | 19.0  | 95   | 0.2587          | 0.975    |
| 0.0           | 20.0  | 100  | 0.2587          | 0.975    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0