---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-Soybean_11-46
  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: 0.9305555555555556
---

<!-- 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. -->

# vit-base-patch16-224-Soybean_11-46

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2058
- Accuracy: 0.9306

## 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: 60
- eval_batch_size: 60
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 240
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3661        | 1.0   | 11   | 1.3698          | 0.5069   |
| 0.9979        | 2.0   | 22   | 0.9817          | 0.6632   |
| 0.6746        | 3.0   | 33   | 0.7423          | 0.7396   |
| 0.6364        | 4.0   | 44   | 0.6075          | 0.7569   |
| 0.5425        | 5.0   | 55   | 0.5500          | 0.7951   |
| 0.5001        | 6.0   | 66   | 0.4883          | 0.8160   |
| 0.3519        | 7.0   | 77   | 0.4539          | 0.8264   |
| 0.4421        | 8.0   | 88   | 0.4483          | 0.8194   |
| 0.3207        | 9.0   | 99   | 0.3785          | 0.8438   |
| 0.3682        | 10.0  | 110  | 0.3385          | 0.8646   |
| 0.2642        | 11.0  | 121  | 0.3827          | 0.8403   |
| 0.3444        | 12.0  | 132  | 0.3462          | 0.8507   |
| 0.2423        | 13.0  | 143  | 0.3170          | 0.8681   |
| 0.3168        | 14.0  | 154  | 0.3168          | 0.8715   |
| 0.2781        | 15.0  | 165  | 0.3323          | 0.8333   |
| 0.2411        | 16.0  | 176  | 0.3200          | 0.8715   |
| 0.2276        | 17.0  | 187  | 0.3296          | 0.875    |
| 0.192         | 18.0  | 198  | 0.3119          | 0.8854   |
| 0.1612        | 19.0  | 209  | 0.3647          | 0.875    |
| 0.1084        | 20.0  | 220  | 0.2641          | 0.8993   |
| 0.2099        | 21.0  | 231  | 0.2807          | 0.8958   |
| 0.1666        | 22.0  | 242  | 0.2595          | 0.9097   |
| 0.1355        | 23.0  | 253  | 0.2735          | 0.8924   |
| 0.1165        | 24.0  | 264  | 0.3238          | 0.8785   |
| 0.112         | 25.0  | 275  | 0.3066          | 0.8889   |
| 0.1191        | 26.0  | 286  | 0.2427          | 0.9062   |
| 0.1293        | 27.0  | 297  | 0.2536          | 0.9201   |
| 0.2932        | 28.0  | 308  | 0.2707          | 0.8924   |
| 0.0918        | 29.0  | 319  | 0.2688          | 0.8924   |
| 0.1529        | 30.0  | 330  | 0.2715          | 0.8889   |
| 0.227         | 31.0  | 341  | 0.2664          | 0.9028   |
| 0.1044        | 32.0  | 352  | 0.2809          | 0.8993   |
| 0.0894        | 33.0  | 363  | 0.2863          | 0.8924   |
| 0.0566        | 34.0  | 374  | 0.2474          | 0.9201   |
| 0.0915        | 35.0  | 385  | 0.2428          | 0.9097   |
| 0.1136        | 36.0  | 396  | 0.2545          | 0.9097   |
| 0.0947        | 37.0  | 407  | 0.2599          | 0.9097   |
| 0.1012        | 38.0  | 418  | 0.2454          | 0.9167   |
| 0.0465        | 39.0  | 429  | 0.2435          | 0.9201   |
| 0.0299        | 40.0  | 440  | 0.2532          | 0.9062   |
| 0.0311        | 41.0  | 451  | 0.2298          | 0.9271   |
| 0.0796        | 42.0  | 462  | 0.2422          | 0.9167   |
| 0.058         | 43.0  | 473  | 0.2058          | 0.9306   |
| 0.0853        | 44.0  | 484  | 0.2266          | 0.9306   |
| 0.0868        | 45.0  | 495  | 0.2266          | 0.9236   |
| 0.0554        | 46.0  | 506  | 0.2163          | 0.9271   |
| 0.0508        | 47.0  | 517  | 0.2104          | 0.9306   |
| 0.0589        | 48.0  | 528  | 0.2172          | 0.9271   |
| 0.0369        | 49.0  | 539  | 0.2214          | 0.9271   |
| 0.0852        | 50.0  | 550  | 0.2241          | 0.9271   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.12.1
- Datasets 2.12.0
- Tokenizers 0.13.1