videomae-base-finetuned-kinetics-0325_final_randomclip

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

• Loss: 0.3441
• Accuracy: 0.9127

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: 8
• eval_batch_size: 8
• 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
• lr_scheduler_warmup_ratio: 0.05
• training_steps: 68700

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0051	0.01	687	0.3061	0.9202
0.0083	1.01	1374	0.5940	0.8527
0.0201	2.01	2061	0.6432	0.8296
1.182	3.01	2748	1.0621	0.7523
0.3175	4.01	3435	1.0938	0.7926
0.0086	5.01	4122	0.4178	0.8815
0.0294	6.01	4809	0.6779	0.8239
0.105	7.01	5496	1.0207	0.8041
0.005	8.01	6183	0.5790	0.8494
0.3475	9.01	6870	1.4327	0.7407
0.5972	10.01	7557	0.7518	0.8543
0.5834	11.01	8244	1.1018	0.7877
0.0075	12.01	8931	0.7481	0.8420
0.5742	13.01	9618	0.9245	0.8058
0.0513	14.01	10305	0.8096	0.8181
0.2228	15.01	10992	0.8514	0.7630

Framework versions

• Transformers 4.48.0
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0