---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: data_classify
  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: 1.0
---

<!-- 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. -->

# identify_stroke

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1127
- Accuracy: 1.0

## Model description

Model identifies cricket shot - front drive, hook shot or sweep shot

## 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: 8
- eval_batch_size: 6
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 0.4345          | 1.0      |
| No log        | 2.0   | 8    | 0.3883          | 1.0      |
| 0.3612        | 3.0   | 12   | 0.4099          | 0.8889   |
| 0.3612        | 4.0   | 16   | 0.2452          | 1.0      |
| 0.2934        | 5.0   | 20   | 0.1969          | 1.0      |
| 0.2934        | 6.0   | 24   | 0.1679          | 1.0      |
| 0.2934        | 7.0   | 28   | 0.1403          | 1.0      |
| 0.203         | 8.0   | 32   | 0.1530          | 1.0      |
| 0.203         | 9.0   | 36   | 0.1161          | 1.0      |
| 0.1505        | 10.0  | 40   | 0.1292          | 1.0      |
| 0.1505        | 11.0  | 44   | 0.1031          | 1.0      |
| 0.1505        | 12.0  | 48   | 0.1084          | 1.0      |
| 0.1388        | 13.0  | 52   | 0.1078          | 1.0      |
| 0.1388        | 14.0  | 56   | 0.0937          | 1.0      |
| 0.1076        | 15.0  | 60   | 0.1008          | 1.0      |
| 0.1076        | 16.0  | 64   | 0.1131          | 1.0      |
| 0.1076        | 17.0  | 68   | 0.1007          | 1.0      |
| 0.1047        | 18.0  | 72   | 0.1775          | 0.8889   |
| 0.1047        | 19.0  | 76   | 0.0844          | 1.0      |
| 0.0902        | 20.0  | 80   | 0.1127          | 1.0      |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3