metadata

library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: videomae-base-finetuned-ucf-crimevbinary-balancedv6
    results: []

videomae-base-finetuned-ucf-crimevbinary-balancedv6

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: 0.6175
Accuracy: 0.8475
Precision: 0.8572
Recall: 0.8475
Auc: 0.9263

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: 3e-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_steps: 500
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	Auc
0.5676	1.0	165	0.5685	0.6608	0.6975	0.6608	0.8059
0.5645	2.0	330	0.3607	0.8481	0.8509	0.8481	0.9362
0.4638	3.0	495	0.5746	0.8021	0.8226	0.8021	0.8919
0.5765	4.0	660	0.3634	0.8622	0.8626	0.8622	0.9262
0.4146	5.0	825	0.5092	0.8092	0.8302	0.8092	0.9225
0.4319	6.0	990	0.4897	0.8799	0.8811	0.8799	0.9316
0.3396	7.0	1155	0.5233	0.8587	0.8599	0.8587	0.9257
0.1152	8.0	1320	0.6568	0.8763	0.8767	0.8763	0.9190
0.0578	9.0	1485	0.6344	0.8693	0.8716	0.8693	0.9321
0.0029	10.0	1650	0.7321	0.8728	0.8739	0.8728	0.9280
0.1363	11.0	1815	0.7399	0.8622	0.8636	0.8622	0.9215

Framework versions

Transformers 4.47.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3