videomae-base-finetuned-fencing

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8879
• Accuracy: 0.6503

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: 12
• eval_batch_size: 12
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 140

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8643	0.2571	36	0.9075	0.6503
0.7975	1.2571	72	0.8868	0.6503
0.9156	2.2571	108	0.8912	0.6503
0.83	3.2286	140	0.8879	0.6503

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1