wav2vec2-base-timit-demo-colab

xacl/wav2vec2-base-timit-demo-colab

wav2vec2-base-timit-demo-colab is a automatic speech recognition model from xacl. 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: wav2vec2
Access: Public
Created: Jul 17, 2023
Updated: Jul 18, 2023
SHA: 183ebc9e

Base models

facebook/wav2vec2-base

Model card

From the Hugging Face model README

wav2vec2-base-timit-demo-colab

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

Loss: 0.5532
Wer: 0.3373
Cer: 0.1112

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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.1293	1.0	500	0.3918	0.3677	0.1170
0.133	2.01	1000	0.4392	0.3797	0.1234
0.1473	3.01	1500	0.4959	0.3914	0.1267
0.1373	4.02	2000	0.4781	0.3851	0.1260
0.1259	5.02	2500	0.4473	0.3810	0.1237
0.1123	6.02	3000	0.5314	0.3774	0.1243
0.1086	7.03	3500	0.4231	0.3801	0.1228
0.0956	8.03	4000	0.5203	0.3734	0.1236
0.0839	9.04	4500	0.5310	0.3750	0.1227
0.0778	10.04	5000	0.5279	0.3793	0.1257
0.0772	11.04	5500	0.4969	0.3792	0.1265
0.072	12.05	6000	0.5489	0.3701	0.1239
0.0678	13.05	6500	0.5123	0.3669	0.1207
0.067	14.06	7000	0.4969	0.3663	0.1192
0.061	15.06	7500	0.4742	0.3664	0.1212
0.0575	16.06	8000	0.5304	0.3643	0.1194
0.0574	17.07	8500	0.4936	0.3729	0.1218
0.0474	18.07	9000	0.5363	0.3601	0.1185
0.0447	19.08	9500	0.5347	0.3552	0.1177
0.0372	20.08	10000	0.5372	0.3519	0.1157
0.0325	21.08	10500	0.5455	0.3525	0.1159
0.0309	22.09	11000	0.5193	0.3514	0.1146
0.0314	23.09	11500	0.5402	0.3494	0.1160
0.0272	24.1	12000	0.5309	0.3457	0.1129
0.0238	25.1	12500	0.5490	0.3447	0.1132
0.0217	26.1	13000	0.5702	0.3406	0.1117
0.0225	27.11	13500	0.5575	0.3414	0.1116
0.0189	28.11	14000	0.5572	0.3391	0.1115
0.0179	29.12	14500	0.5532	0.3373	0.1112

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu118
Datasets 1.18.3
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Jul 17, 2023
Updated: Jul 18, 2023