---
license: apache-2.0
base_model: google/vit-base-patch16-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-vit-base-patch16-384-finetuned-spiderTraining20-500
  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. -->

# 10-vit-base-patch16-384-finetuned-spiderTraining20-500

This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3427
- Accuracy: 0.9029
- Precision: 0.9012
- Recall: 0.9032
- F1: 0.9009

## 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: 0.0005
- train_batch_size: 25
- eval_batch_size: 25
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6925        | 1.0   | 80   | 0.6605          | 0.7938   | 0.8012    | 0.7887 | 0.7869 |
| 0.5869        | 2.0   | 160  | 0.5574          | 0.8298   | 0.8350    | 0.8254 | 0.8214 |
| 0.4858        | 3.0   | 240  | 0.4335          | 0.8689   | 0.8692    | 0.8644 | 0.8644 |
| 0.3921        | 4.0   | 320  | 0.4455          | 0.8739   | 0.8737    | 0.8722 | 0.8699 |
| 0.2915        | 5.0   | 400  | 0.4707          | 0.8629   | 0.8708    | 0.8612 | 0.8571 |
| 0.2727        | 6.0   | 480  | 0.4471          | 0.8819   | 0.8795    | 0.8808 | 0.8777 |
| 0.216         | 7.0   | 560  | 0.3809          | 0.8899   | 0.8879    | 0.8874 | 0.8862 |
| 0.1685        | 8.0   | 640  | 0.3760          | 0.8949   | 0.8938    | 0.8934 | 0.8915 |
| 0.1292        | 9.0   | 720  | 0.3427          | 0.9049   | 0.9034    | 0.9032 | 0.9021 |
| 0.1321        | 10.0  | 800  | 0.3427          | 0.9029   | 0.9012    | 0.9032 | 0.9009 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3