This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5231
Accuracy: 0.8377

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8248	0.99	78	0.7299	0.7667
0.806	1.99	157	0.6541	0.7944
0.8544	3.0	236	0.6443	0.7996
0.8503	4.0	315	0.5965	0.8179
0.7538	4.99	393	0.5674	0.8282
0.6921	5.99	472	0.5941	0.8175
0.7214	7.0	551	0.5721	0.8246
0.6402	8.0	630	0.5433	0.8361
0.5899	8.99	708	0.5323	0.8425
0.6688	9.99	787	0.5213	0.8409
0.5948	11.0	866	0.5244	0.8385
0.5818	11.89	936	0.5231	0.8377

Framework versions

Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

luciagil/Human-action-swin

Human-action-swin

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

luciagil/
Human-action-swin