---
library_name: transformers
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: beit-base-patch16-224-pt22k-ft22k-finetuned-barkley
  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. -->

# beit-base-patch16-224-pt22k-ft22k-finetuned-barkley

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0079
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
- Top1 Accuracy: 1.0
- Error Rate: 0.0

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 1.5547        | 1.0   | 38   | 1.4018          | 0.5683    | 0.4539 | 0.4240 | 0.4728   | 0.4539        | 0.5272     |
| 1.1732        | 2.0   | 76   | 0.9193          | 0.8095    | 0.7961 | 0.7985 | 0.8077   | 0.7961        | 0.1923     |
| 0.6764        | 3.0   | 114  | 0.3644          | 0.9488    | 0.9474 | 0.9470 | 0.9483   | 0.9474        | 0.0517     |
| 0.2566        | 4.0   | 152  | 0.0871          | 0.9937    | 0.9934 | 0.9934 | 0.9944   | 0.9934        | 0.0056     |
| 0.1014        | 5.0   | 190  | 0.0533          | 0.9809    | 0.9803 | 0.9802 | 0.9811   | 0.9803        | 0.0189     |
| 0.0538        | 6.0   | 228  | 0.0208          | 1.0       | 1.0    | 1.0    | 1.0      | 1.0           | 0.0        |
| 0.0304        | 7.0   | 266  | 0.0079          | 1.0       | 1.0    | 1.0    | 1.0      | 1.0           | 0.0        |
| 0.0571        | 8.0   | 304  | 0.0088          | 1.0       | 1.0    | 1.0    | 1.0      | 1.0           | 0.0        |
| 0.0608        | 9.0   | 342  | 0.0226          | 0.9936    | 0.9934 | 0.9934 | 0.9933   | 0.9934        | 0.0067     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1