whisper-tiny-en-US

sumet/whisper-tiny-en-US

whisper-tiny-en-US is a automatic speech recognition model from sumet. 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: Jul 12, 2023
Updated: Jul 12, 2023
SHA: f2f8ea0c

Base models

openai/whisper-tiny

Datasets

PolyAI/minds14

Model card

From the Hugging Face model README

whisper-tiny-en-US

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

Loss: 0.4245
Wer Ortho: 0.1714
Wer: 0.1655

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 5
training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
No log	0.36	10	3.1022	0.3282	0.1960
No log	0.71	20	1.6867	0.2399	0.1865
2.9245	1.07	30	0.6685	0.2332	0.1982
2.9245	1.43	40	0.4912	0.2017	0.1848
0.6297	1.79	50	0.4243	0.1865	0.1753
0.6297	2.14	60	0.3895	0.1801	0.1689
0.6297	2.5	70	0.3678	0.1769	0.1669
0.3045	2.86	80	0.3570	0.1746	0.1689
0.3045	3.21	90	0.3496	0.1720	0.1647
0.1949	3.57	100	0.3451	0.1746	0.1661
0.1949	3.93	110	0.3407	0.1804	0.1700
0.1949	4.29	120	0.3439	0.1778	0.1695
0.1099	4.64	130	0.3501	0.1743	0.1689
0.1099	5.0	140	0.3488	0.1737	0.1667
0.0583	5.36	150	0.3554	0.1778	0.1697
0.0583	5.71	160	0.3595	0.1708	0.1628
0.0583	6.07	170	0.3514	0.1746	0.1661
0.032	6.43	180	0.3672	0.1755	0.1683
0.032	6.79	190	0.3676	0.1676	0.1602
0.0146	7.14	200	0.3791	0.1658	0.1600
0.0146	7.5	210	0.3825	0.1676	0.1625
0.0146	7.86	220	0.3799	0.1702	0.1650
0.0084	8.21	230	0.3827	0.1702	0.1655
0.0084	8.57	240	0.3869	0.1778	0.1714
0.0043	8.93	250	0.3951	0.1740	0.1686
0.0043	9.29	260	0.3958	0.1720	0.1672
0.0043	9.64	270	0.3968	0.1758	0.1706
0.003	10.0	280	0.3978	0.1725	0.1672
0.003	10.36	290	0.4012	0.1734	0.1681
0.0023	10.71	300	0.4068	0.1728	0.1678
0.0023	11.07	310	0.4097	0.1752	0.1697
0.0023	11.43	320	0.4113	0.1746	0.1692
0.0018	11.79	330	0.4120	0.1737	0.1681
0.0018	12.14	340	0.4141	0.1740	0.1683
0.0016	12.5	350	0.4172	0.1731	0.1678
0.0016	12.86	360	0.4193	0.1740	0.1681
0.0016	13.21	370	0.4197	0.1731	0.1672
0.0014	13.57	380	0.4215	0.1731	0.1672
0.0014	13.93	390	0.4228	0.1720	0.1664
0.0012	14.29	400	0.4245	0.1714	0.1655

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: whisper
License: apache-2.0
Created: Jul 12, 2023
Updated: Jul 12, 2023