This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the speech_commands dataset. It achieves the following results on the evaluation set:

Loss: 0.4825
Accuracy: 0.8890

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: 72
eval_batch_size: 72
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 288
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3557	1.0	294	0.7017	0.8354
0.1948	2.0	589	0.6838	0.8397
0.1219	3.0	884	0.5752	0.8699
0.0704	4.0	1179	0.5554	0.8675
0.0404	5.0	1473	0.5437	0.8663
0.0136	6.0	1768	0.5247	0.8759
0.0072	7.0	2063	0.5235	0.8759
0.0026	8.0	2358	0.5035	0.8859
0.0007	9.0	2652	0.4800	0.8896
0.0005	9.97	2940	0.4825	0.8890

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.14.6
Tokenizers 0.14.1

moonseok/AST_speechcommandsV2_final

AST_speechcommandsV2_final

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

moonseok/
AST_speechcommandsV2_final