| | --- |
| | 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 |
| |
|
