metadata

license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-base-finetuned-good-gesturePhaseV3
    results: []

videomae-base-finetuned-good-gesturePhaseV3

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:

Accuracy: 0.6939
Loss: 0.9297
Accuracy Hold: 0.0
Accuracy Stroke: 0.0
Accuracy Recovery: 0.0
Accuracy Preparation: 0.8961
Accuracy Unknown: 0.9429

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
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: 690

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss	Accuracy Preparation	Accuracy Unknown
1.0859	0.1014	70	0.5597	1.2821	1.0	0.0
1.1816	1.1014	140	0.5597	1.2569	1.0	0.0
0.9776	2.1014	210	0.5597	1.1835	1.0	0.0
0.9867	3.1014	280	0.6119	1.0721	0.96	0.3846
1.0732	4.1014	350	0.6045	1.1086	0.7333	1.0
0.9688	5.1014	420	0.6866	0.9288	0.9333	0.8462
0.7733	6.1014	490	0.6567	0.9749	0.8267	1.0
0.8798	7.1014	560	0.6866	0.8742	0.92	0.8846
0.7771	8.1014	630	0.7015	0.8452	0.92	0.9615
1.0448	9.0870	690	0.7239	0.8357	0.96	0.9615

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1