vivit-b-16x2-kinetics400-finetuned-cricket_shot_detection_12
This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9751
- Accuracy: 0.5789
- F1: 0.5857
- Recall: 0.5789
- Precision: 0.6053
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: 7e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1152
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
---|---|---|---|---|---|---|---|
1.3542 | 0.1259 | 145 | 1.2326 | 0.4737 | 0.5160 | 0.4737 | 0.6 |
0.6744 | 1.1259 | 290 | 1.1345 | 0.4737 | 0.4793 | 0.4737 | 0.5545 |
0.5513 | 2.1259 | 435 | 0.9751 | 0.5789 | 0.5857 | 0.5789 | 0.6053 |
0.3373 | 3.1259 | 580 | 0.9298 | 0.5789 | 0.5807 | 0.5789 | 0.6 |
0.4953 | 4.1259 | 725 | 0.9415 | 0.5789 | 0.6003 | 0.5789 | 0.6526 |
0.336 | 5.1259 | 870 | 0.8837 | 0.5789 | 0.5857 | 0.5789 | 0.6053 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- 9
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for Asadali12/vivit-b-16x2-kinetics400-finetuned-cricket_shot_detection_12
Base model
google/vivit-b-16x2-kinetics400