videomae-base-constanza-aumentado

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: 0.5739
• Accuracy: 0.8929

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: 0.1
• training_steps: 700

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.2747	0.1014	71	1.4731	0.2143
0.3265	1.1014	142	0.3557	0.9286
0.1731	2.1014	213	0.1865	0.9286
0.0052	3.1014	284	0.2003	0.9286
0.0027	4.1014	355	0.0026	1.0
0.0015	5.1014	426	0.0037	1.0
0.0019	6.1014	497	0.0015	1.0
0.0211	7.1014	568	0.0027	1.0
0.0009	8.1014	639	0.0017	1.0
0.0569	9.0871	700	0.0015	1.0

Framework versions

• Transformers 4.46.2
• Pytorch 2.0.1+cu117
• Datasets 3.1.0
• Tokenizers 0.20.3