---
license: apache-2.0
base_model: microsoft/cvt-21-384-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cvt-21-384-22k-finetuned-LeafType
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9310344827586207
---

<!-- 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. -->

# cvt-21-384-22k-finetuned-LeafType

This model is a fine-tuned version of [microsoft/cvt-21-384-22k](https://huggingface.co/microsoft/cvt-21-384-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2232
- Accuracy: 0.9310

## 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: 2e-05
- train_batch_size: 160
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 11   | 0.4857          | 0.7586   |
| No log        | 2.0   | 22   | 0.2275          | 0.9163   |
| No log        | 3.0   | 33   | 0.2791          | 0.8867   |
| No log        | 4.0   | 44   | 0.3083          | 0.8522   |
| No log        | 5.0   | 55   | 0.1496          | 0.9458   |
| No log        | 6.0   | 66   | 0.2092          | 0.8966   |
| No log        | 7.0   | 77   | 0.3349          | 0.8522   |
| No log        | 8.0   | 88   | 0.1513          | 0.9557   |
| No log        | 9.0   | 99   | 0.1385          | 0.9557   |
| No log        | 10.0  | 110  | 0.1676          | 0.9360   |
| No log        | 11.0  | 121  | 0.1284          | 0.9507   |
| No log        | 12.0  | 132  | 0.1981          | 0.9015   |
| No log        | 13.0  | 143  | 0.1346          | 0.9360   |
| No log        | 14.0  | 154  | 0.3235          | 0.8621   |
| No log        | 15.0  | 165  | 0.1506          | 0.9310   |
| No log        | 16.0  | 176  | 0.1536          | 0.9360   |
| No log        | 17.0  | 187  | 0.1529          | 0.9458   |
| No log        | 18.0  | 198  | 0.2431          | 0.8966   |
| No log        | 19.0  | 209  | 0.2251          | 0.9163   |
| No log        | 20.0  | 220  | 0.2068          | 0.9163   |
| No log        | 21.0  | 231  | 0.1429          | 0.9458   |
| No log        | 22.0  | 242  | 0.2078          | 0.9163   |
| No log        | 23.0  | 253  | 0.1428          | 0.9360   |
| No log        | 24.0  | 264  | 0.2391          | 0.8916   |
| No log        | 25.0  | 275  | 0.1512          | 0.9458   |
| No log        | 26.0  | 286  | 0.1512          | 0.9458   |
| No log        | 27.0  | 297  | 0.1303          | 0.9606   |
| No log        | 28.0  | 308  | 0.2381          | 0.8867   |
| No log        | 29.0  | 319  | 0.1544          | 0.9458   |
| No log        | 30.0  | 330  | 0.2149          | 0.8916   |
| No log        | 31.0  | 341  | 0.1387          | 0.9557   |
| No log        | 32.0  | 352  | 0.1698          | 0.9360   |
| No log        | 33.0  | 363  | 0.1750          | 0.9409   |
| No log        | 34.0  | 374  | 0.2041          | 0.9113   |
| No log        | 35.0  | 385  | 0.1888          | 0.9360   |
| No log        | 36.0  | 396  | 0.1527          | 0.9458   |
| No log        | 37.0  | 407  | 0.1721          | 0.9360   |
| No log        | 38.0  | 418  | 0.1720          | 0.9409   |
| No log        | 39.0  | 429  | 0.1810          | 0.9360   |
| No log        | 40.0  | 440  | 0.2041          | 0.9261   |
| No log        | 41.0  | 451  | 0.1945          | 0.9261   |
| No log        | 42.0  | 462  | 0.2211          | 0.9163   |
| No log        | 43.0  | 473  | 0.2284          | 0.9163   |
| No log        | 44.0  | 484  | 0.1905          | 0.9261   |
| No log        | 45.0  | 495  | 0.2329          | 0.9113   |
| 0.2716        | 46.0  | 506  | 0.1839          | 0.9360   |
| 0.2716        | 47.0  | 517  | 0.1854          | 0.9310   |
| 0.2716        | 48.0  | 528  | 0.1923          | 0.9310   |
| 0.2716        | 49.0  | 539  | 0.2254          | 0.9261   |
| 0.2716        | 50.0  | 550  | 0.2677          | 0.9015   |
| 0.2716        | 51.0  | 561  | 0.2620          | 0.9015   |
| 0.2716        | 52.0  | 572  | 0.2224          | 0.9261   |
| 0.2716        | 53.0  | 583  | 0.2238          | 0.9310   |
| 0.2716        | 54.0  | 594  | 0.2355          | 0.9212   |
| 0.2716        | 55.0  | 605  | 0.2533          | 0.9261   |
| 0.2716        | 56.0  | 616  | 0.2237          | 0.9310   |
| 0.2716        | 57.0  | 627  | 0.2296          | 0.9310   |
| 0.2716        | 58.0  | 638  | 0.2361          | 0.9310   |
| 0.2716        | 59.0  | 649  | 0.2358          | 0.9310   |
| 0.2716        | 60.0  | 660  | 0.2232          | 0.9310   |


### Framework versions

- Transformers 4.38.1
- Pytorch 1.10.0+cu111
- Datasets 2.17.1
- Tokenizers 0.15.2