hubert-base-timit-demo-google-colab-ft30ep_v4

danieleV9H/hubert-base-timit-demo-google-colab-ft30ep_v4

hubert-base-timit-demo-google-colab-ft30ep_v4 is a automatic speech recognition model from danieleV9H. Use it when you need speech turned into text. 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. --

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: hubert
Access: Public
Created: May 11, 2022
Updated: May 14, 2022
SHA: 66ff2e38

Model card

From the Hugging Face model README

hubert-base-timit-demo-google-colab-ft35ep

This model is a fine-tuned version of facebook/hubert-base-ls960 on the timit-asr dataset. It achieves the following results on the evaluation set:

Loss: 0.4602
Wer: 0.3466

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.825	0.87	500	2.9521	1.0
2.431	1.73	1000	0.9760	0.8013
1.0089	2.6	1500	0.5934	0.5968
0.6859	3.46	2000	0.5132	0.5356
0.5302	4.33	2500	0.4506	0.4894
0.44	5.19	3000	0.4340	0.4670
0.3926	6.06	3500	0.4506	0.4528
0.3326	6.92	4000	0.4197	0.4486
0.2937	7.79	4500	0.4093	0.4193
0.2568	8.65	5000	0.4098	0.4229
0.2473	9.52	5500	0.4090	0.4141
0.2233	10.38	6000	0.4152	0.4125
0.2108	11.25	6500	0.4586	0.4189
0.2086	12.11	7000	0.4284	0.3969
0.1858	12.98	7500	0.4028	0.3946
0.1641	13.84	8000	0.4679	0.4002
0.1686	14.71	8500	0.4441	0.3936
0.1489	15.57	9000	0.4897	0.3828
0.1541	16.44	9500	0.4953	0.3783
0.1417	17.3	10000	0.4500	0.3758
0.1428	18.17	10500	0.4533	0.3796
0.1306	19.03	11000	0.4474	0.3792
0.1185	19.9	11500	0.4762	0.3743
0.1081	20.76	12000	0.4770	0.3699
0.1253	21.63	12500	0.4749	0.3629
0.1087	22.49	13000	0.4577	0.3534
0.1172	23.36	13500	0.4819	0.3525
0.1086	24.22	14000	0.4709	0.3623
0.089	25.09	14500	0.4852	0.3544
0.086	25.95	15000	0.4602	0.3555
0.086	26.82	15500	0.4861	0.3497
0.086	27.68	16000	0.4527	0.3473
0.0919	28.55	16500	0.4607	0.3487
0.0792	29.41	17000	0.4602	0.3466

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 1.18.3
Tokenizers 0.12.1

Task: Automatic Speech Recognition
Library: transformers
Type: hubert
License: apache-2.0
Created: May 11, 2022
Updated: May 14, 2022