wav2vec2-ver2.0-paper

hts98/wav2vec2-ver2.0-paper

wav2vec2-ver2.0-paper is a automatic speech recognition model from hts98. 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: Jun 26, 2023
Updated: Jul 1, 2023
SHA: d91d16f3

Model card

From the Hugging Face model README

wav2vec2-ver2.0

This model is a fine-tuned version of facebook/wav2vec2-base on the HTS98/ORIGINAL_VER1.2 - NA dataset. It achieves the following results on the evaluation set:

Loss: 0.9210
Wer: 0.3901

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: 5e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 50.0

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.99	104	4.0281	1.0
No log	2.0	209	3.4058	1.0
No log	2.99	312	3.3457	1.0
No log	4.0	417	3.3384	1.0
3.351	5.0	522	3.3195	1.0
3.351	6.0	627	3.2774	1.0000
3.351	6.99	731	2.7498	1.0184
3.351	8.0	836	2.0695	0.9268
3.351	9.0	941	1.6666	0.8103
2.5482	10.0	1046	1.4119	0.7014
2.5482	10.99	1150	1.2480	0.6408
2.5482	12.0	1255	1.1397	0.5814
2.5482	13.0	1360	1.0593	0.5381
2.5482	14.0	1465	1.0060	0.5099
1.1172	14.99	1569	0.9678	0.4830
1.1172	16.0	1674	0.9379	0.4692
1.1172	17.0	1779	0.9127	0.4618
1.1172	18.0	1884	0.8923	0.4352
1.1172	18.99	1988	0.8827	0.4254
0.7161	20.0	2093	0.8722	0.4304
0.7161	21.0	2198	0.8755	0.4142
0.7161	22.0	2303	0.8680	0.4157
0.7161	22.99	2407	0.8705	0.4116
0.5338	24.0	2512	0.8611	0.4039
0.5338	25.0	2617	0.8716	0.3995
0.5338	26.0	2722	0.8721	0.4037
0.5338	26.99	2826	0.8809	0.3973
0.5338	28.0	2931	0.9037	0.3938
0.4299	29.0	3036	0.9119	0.3903
0.4299	30.0	3141	0.9117	0.3912
0.4299	30.99	3245	0.9027	0.3930
0.4299	31.99	3328	0.9240	0.3898
0.4299	33.0	3433	0.9337	0.3872
0.3491	34.0	3538	0.9210	0.3901
0.3491	35.0	3643	0.9309	0.3905
0.3491	35.99	3747	0.9528	0.3906
0.3491	37.0	3852	0.9506	0.3880
0.3491	38.0	3957	0.9607	0.3853
0.3195	39.0	4062	0.9567	0.3906
0.3195	39.99	4166	0.9632	0.3893
0.3195	41.0	4271	0.9797	0.3839
0.3195	42.0	4376	0.9819	0.3854
0.3195	43.0	4481	0.9686	0.3870
0.2892	43.99	4585	0.9808	0.3895
0.2892	45.0	4690	0.9857	0.3892
0.2892	46.0	4795	0.9959	0.3831
0.2892	47.0	4900	0.9959	0.3870
0.2705	47.99	5004	1.0028	0.3860
0.2705	49.0	5109	1.0019	0.3869
0.2705	49.86	5200	1.0050	0.3857

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.7.0
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Jun 26, 2023
Updated: Jul 1, 2023