wav2vec2-base-random-stopvoicing-1

This model is a fine-tuned version of on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.3669
• Accuracy: 0.8702

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 24

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6871	0.99	20	0.6530	0.6213
0.6757	1.98	40	0.6507	0.6104
0.6193	2.96	60	0.4827	0.7691
0.5511	4.0	81	0.4494	0.7950
0.5076	4.99	101	0.4027	0.8283
0.4882	5.98	121	0.5145	0.7813
0.4728	6.96	141	0.4394	0.8120
0.4351	8.0	162	0.4163	0.8270
0.4432	8.99	182	0.3823	0.8392
0.4165	9.98	202	0.4307	0.8263
0.3947	10.96	222	0.3569	0.8604
0.4186	12.0	243	0.4431	0.8283
0.3948	12.99	263	0.3836	0.8522
0.3627	13.98	283	0.3778	0.8569
0.3922	14.96	303	0.3523	0.8624
0.3668	16.0	324	0.3543	0.8631
0.3676	16.99	344	0.3485	0.8610
0.3118	17.98	364	0.3838	0.8638
0.328	18.96	384	0.3509	0.8685
0.3387	20.0	405	0.3593	0.8685
0.3088	20.99	425	0.3596	0.8631
0.2942	21.98	445	0.3585	0.8713
0.3027	22.96	465	0.3644	0.8651
0.2913	23.7	480	0.3575	0.8692

Framework versions

• Transformers 4.27.4
• Pytorch 1.13.0
• Datasets 2.7.1
• Tokenizers 0.13.2