wav2vec2-base-random-stop-classification-4 – AI Model by suyuanliu | AlphaNeural AI

You can deploy this model and start earning money today!

suyuanliu/
wav2vec2-base-random-stop-classification-4

like

0

audio-classification

generated_from_trainer

endpoints_compatible

Views

No views yet

wav2vec2-base-random-stop-classification-4

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

Loss: 0.3843
Accuracy: 0.8706

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: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6928	0.99	18	0.6588	0.6267
0.6746	1.97	36	0.5702	0.6969
0.5823	2.96	54	0.5035	0.7772
0.5573	4.0	73	0.4111	0.8188
0.5324	4.99	91	0.4359	0.7997
0.6058	5.97	109	0.4688	0.7875
0.4805	6.96	127	0.4055	0.8351
0.4641	8.0	146	0.4024	0.8351
0.4292	8.99	164	0.3913	0.8474
0.4217	9.97	182	0.3975	0.8522
0.3892	10.96	200	0.3808	0.8460
0.4056	12.0	219	0.4126	0.8515
0.3848	12.99	237	0.3602	0.8508
0.3698	13.97	255	0.3913	0.8488
0.3893	14.96	273	0.3611	0.8692
0.3341	16.0	292	0.3791	0.8624
0.3376	16.99	310	0.3578	0.8624
0.3331	17.97	328	0.3660	0.8658
0.3215	18.96	346	0.3817	0.8535
0.2982	20.0	365	0.4000	0.8658
0.2885	20.99	383	0.3674	0.8658
0.3124	21.97	401	0.3770	0.8672
0.2926	22.96	419	0.3779	0.8651
0.2941	24.0	438	0.3775	0.8733
0.2699	24.66	450	0.3843	0.8706

Framework versions

Transformers 4.27.4
Pytorch 1.13.0
Datasets 2.7.1
Tokenizers 0.13.2