whisper_data_self_tiny

manhvh2601/whisper_data_self_tiny

whisper_data_self_tiny is a automatic speech recognition model from manhvh2601. 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: whisper
Access: Public
Created: Jan 23, 2024
Updated: Jan 25, 2024
SHA: c3eae89c

Base models

openai/whisper-small

Model card

From the Hugging Face model README

Whisper Vietnamese Vu Hoang Manh

This model is a fine-tuned version of openai/whisper-small on the Vietnamese ASR dataset. It achieves the following results on the evaluation set:

Loss: 0.0549
Wer: 8.9064

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: 0.0003
train_batch_size: 16
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: 50
training_steps: 5250
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1693	1.0	105	0.1621	224.6900
0.1317	2.0	210	0.0764	26.2683
0.0868	3.0	315	0.1650	26.3247
0.0645	4.0	420	0.0592	43.7993
0.0578	5.0	525	0.0755	41.0372
0.0342	6.0	630	0.0640	29.2559
0.0325	7.0	735	0.0514	13.1342
0.0397	8.0	840	0.0587	37.8241
0.0307	9.0	945	0.0628	32.1308
0.0215	10.0	1050	0.0742	23.8444
0.0268	11.0	1155	0.0710	35.6257
0.009	12.0	1260	0.0539	11.9504
0.0084	13.0	1365	0.0705	16.2345
0.0158	14.0	1470	0.0489	20.6877
0.0122	15.0	1575	0.0582	10.3720
0.0139	16.0	1680	0.0620	17.1928
0.0121	17.0	1785	0.0734	16.0654
0.0055	18.0	1890	0.0719	32.6381
0.0044	19.0	1995	0.0614	83.5964
0.0083	20.0	2100	0.0930	22.3224
0.0081	21.0	2205	0.0872	14.2616
0.0112	22.0	2310	0.0417	17.4183
0.0076	23.0	2415	0.0698	13.6979
0.0043	24.0	2520	0.0428	9.1319
0.0005	25.0	2625	0.0466	9.5829
0.0002	26.0	2730	0.0597	11.2176
0.0	27.0	2835	0.0527	10.0338
0.0	28.0	2940	0.0521	9.4138
0.0	29.0	3045	0.0523	9.4138
0.0	30.0	3150	0.0526	9.3574
0.0	31.0	3255	0.0527	9.4138
0.0	32.0	3360	0.0529	9.3574
0.0	33.0	3465	0.0531	9.3010
0.0	34.0	3570	0.0533	9.2446
0.0	35.0	3675	0.0535	9.1883
0.0	36.0	3780	0.0537	9.1319
0.0	37.0	3885	0.0538	9.0755
0.0	38.0	3990	0.0540	9.0192
0.0	39.0	4095	0.0541	9.0192
0.0	40.0	4200	0.0542	9.0192
0.0	41.0	4305	0.0543	9.0192
0.0	42.0	4410	0.0544	9.0192
0.0	43.0	4515	0.0545	8.9064
0.0	44.0	4620	0.0546	8.9064
0.0	45.0	4725	0.0547	8.9064
0.0	46.0	4830	0.0548	8.9064
0.0	47.0	4935	0.0549	8.9064
0.0	48.0	5040	0.0549	8.9064
0.0	49.0	5145	0.0549	8.7937
0.0	50.0	5250	0.0549	8.9064

Framework versions

Transformers 4.38.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1

Task: Automatic Speech Recognition
Library: transformers
Type: whisper
License: apache-2.0
Languages: vi
Created: Jan 23, 2024
Updated: Jan 25, 2024