audioclass-alpha

giovaldir/audioclass-alpha

audioclass-alpha is a audio classification model from giovaldir. Use it for the audio 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 apache-2.0.

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

Downloads · 30 days

12% of all-time downloads

All-time downloads

Public

Parameters

94.6M

38.2 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors378 MB · 100%

At a glance

Task: Audio Classification
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Nov 5, 2023
Updated: Nov 5, 2023
SHA: b2438636

Base models

facebook/wav2vec2-base-960h

Model card

From the Hugging Face model README

audioclass-alpha

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0963
Accuracy: 0.9819

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.3678	1.0	62	3.3612	0.0408
3.349	2.0	124	3.3402	0.0385
3.2935	3.0	186	3.2047	0.2494
2.9643	4.0	248	2.7250	0.5102
2.4158	5.0	310	2.1914	0.6621
1.9634	6.0	372	1.7440	0.7800
1.6144	7.0	434	1.3680	0.8503
1.2939	8.0	496	1.0948	0.8390
1.0933	9.0	558	0.8783	0.8776
0.8596	10.0	620	0.7053	0.9048
0.6664	11.0	682	0.6020	0.9184
0.5843	12.0	744	0.5392	0.9048
0.5714	13.0	806	0.4380	0.9297
0.4395	14.0	868	0.4434	0.9252
0.323	15.0	930	0.3000	0.9524
0.3218	16.0	992	0.2418	0.9546
0.3026	17.0	1054	0.2462	0.9524
0.2531	18.0	1116	0.2003	0.9660
0.2702	19.0	1178	0.1883	0.9637
0.2368	20.0	1240	0.1612	0.9728
0.2121	21.0	1302	0.1981	0.9637
0.2011	22.0	1364	0.1635	0.9683
0.1875	23.0	1426	0.1454	0.9728
0.1415	24.0	1488	0.1433	0.9683
0.1162	25.0	1550	0.1504	0.9660
0.0946	26.0	1612	0.1759	0.9615
0.1032	27.0	1674	0.1206	0.9751
0.095	28.0	1736	0.1123	0.9773
0.1526	29.0	1798	0.1267	0.9728
0.1003	30.0	1860	0.0953	0.9796
0.1371	31.0	1922	0.1158	0.9751
0.0765	32.0	1984	0.0963	0.9819
0.1152	33.0	2046	0.0929	0.9819
0.1344	34.0	2108	0.1103	0.9796
0.1067	35.0	2170	0.1065	0.9773
0.0847	36.0	2232	0.0898	0.9819
0.0835	37.0	2294	0.0934	0.9819
0.1009	38.0	2356	0.1136	0.9796
0.1272	39.0	2418	0.1315	0.9751
0.0463	40.0	2480	0.1127	0.9796
0.085	41.0	2542	0.0985	0.9796
0.0431	42.0	2604	0.0964	0.9773
0.0698	43.0	2666	0.1128	0.9773
0.0493	44.0	2728	0.0934	0.9796
0.1208	45.0	2790	0.0882	0.9819
0.0536	46.0	2852	0.0932	0.9796
0.064	47.0	2914	0.1008	0.9796
0.0538	48.0	2976	0.1094	0.9796
0.0774	49.0	3038	0.1081	0.9796
0.0379	50.0	3100	0.1085	0.9796

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

Task: Audio Classification
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Nov 5, 2023
Updated: Nov 5, 2023