videomae-base-finetuned-soccer-action-recognitionx4

anirudhmu/videomae-base-finetuned-soccer-action-recognitionx4

videomae-base-finetuned-soccer-action-recognitionx4 is a video classification model from anirudhmu. Use it for the video classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-nc-4.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Video Classification
Library: transformers
License: cc-by-nc-4.0
Model type: videomae
Access: Public
Created: Nov 15, 2023
Updated: Nov 16, 2023
SHA: deb26e99

Base models

MCG-NJU/videomae-base

Model card

From the Hugging Face model README

videomae-base-finetuned-soccer-action-recognitionx4

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: 0.1327
Accuracy: 0.9648

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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 1125

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.02	28	1.3255	0.3782
No log	1.02	56	0.9903	0.5751
1.1078	2.02	84	0.4648	0.8238
1.1078	3.03	113	0.4075	0.8342
1.1078	4.02	141	0.2301	0.9275
0.2591	5.02	169	0.4090	0.8549
0.2591	6.02	197	0.1527	0.9482
0.2591	7.03	226	0.1413	0.9585
0.111	8.02	254	0.1386	0.9637
0.111	9.02	282	0.1674	0.9430
0.111	10.02	310	0.1010	0.9741
0.0509	11.03	339	0.1586	0.9637
0.0509	12.02	367	0.2696	0.8860
0.0509	13.02	395	0.3005	0.9171
0.023	14.02	423	0.1001	0.9741
0.023	15.03	452	0.1961	0.9482
0.0354	16.02	480	0.2596	0.9223
0.0354	17.02	508	0.1006	0.9689
0.0354	18.02	536	0.0947	0.9793
0.0141	19.03	565	0.0831	0.9793
0.0141	20.02	593	0.0685	0.9793
0.0141	21.02	621	0.0978	0.9689
0.0168	22.02	649	0.0812	0.9793
0.0168	23.03	678	0.0782	0.9793
0.0168	24.02	706	0.2624	0.9275
0.0029	25.02	734	0.1806	0.9534
0.0029	26.02	762	0.2123	0.9585
0.0029	27.03	791	0.2010	0.9482
0.0048	28.02	819	0.1259	0.9689
0.0048	29.02	847	0.2145	0.9430
0.0048	30.02	875	0.2901	0.9223
0.0042	31.03	904	0.0911	0.9793
0.0042	32.02	932	0.0892	0.9741
0.0024	33.02	960	0.0911	0.9845
0.0024	34.02	988	0.0987	0.9741
0.0024	35.03	1017	0.1446	0.9482
0.0008	36.02	1045	0.1415	0.9482
0.0008	37.02	1073	0.1435	0.9482
0.0008	38.02	1101	0.1438	0.9482
0.0008	39.02	1125	0.1371	0.9534

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.14.7
Tokenizers 0.15.0

Task: Video Classification
Library: transformers
Type: videomae
License: cc-by-nc-4.0
Created: Nov 15, 2023
Updated: Nov 16, 2023