Model reference · open weights

unispeech-large-1500h-cv-tim

Name: unispeech-large-1500h-cv-tim
Brand: AxForge

Available as managed deployment Audio patrickvonplaten · community Speech→text 1 variants 684 dl/mo

unispeech-large-1500h-cv-tim is an open-weight audio or speech model from patrickvonplaten. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

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Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released by	patrickvonplaten
Type	Audio & music
Task	Speech→text
Runs with	transformers
Released	2022-03-02
Popularity	684 downloads / month
Licence	Unknown

About

What unispeech-large-1500h-cv-tim is

This model is a fine-tuned version of microsoft/unispeech-large-1500h-cv on the TIMIT_ASR - NA dataset. It achieves the following results on the evaluation set:

Loss: 0.3099
Wer: 0.2196

Read the full model card

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: 32
eval_batch_size: 1
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: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.64	0.69	100	3.9717	0.9981
2.6793	1.38	200	2.6264	1.0
1.2221	2.07	300	0.9999	0.7167
0.9009	2.76	400	0.6509	0.5570
0.4352	3.45	500	0.4682	0.4332
0.227	4.14	600	0.3661	0.3565
0.2169	4.83	700	0.3244	0.3203
0.2687	5.52	800	0.3137	0.2981
0.127	6.21	900	0.3220	0.2828
0.0922	6.9	1000	0.3075	0.2708
0.0965	7.59	1100	0.2779	0.2576
0.1298	8.28	1200	0.3111	0.2480
0.0855	8.97	1300	0.3021	0.2421
0.0629	9.66	1400	0.3122	0.2511
0.0471	10.34	1500	0.2965	0.2368
0.0871	11.03	1600	0.3247	0.2387
0.0503	11.72	1700	0.3359	0.2363
0.0402	12.41	1800	0.2976	0.2332
0.0336	13.1	1900	0.3139	0.2321
0.0634	13.79	2000	0.3188	0.2309
0.0429	14.48	2100	0.3145	0.2335
0.028	15.17	2200	0.3244	0.2242
0.0255	15.86	2300	0.2914	0.2196
0.0406	16.55	2400	0.3249	0.2202
0.0512	17.24	2500	0.3037	0.2198
0.0269	17.93	2600	0.3218	0.2242
0.0287	18.62	2700	0.3106	0.2185
0.0319	19.31	2800	0.3124	0.2217
0.0494	20.0	2900	0.3099	0.2196

Framework versions

Transformers 4.12.0.dev0
Pytorch 1.8.1
Datasets 1.14.1.dev0
Tokenizers 0.10.3

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys unispeech-large-1500h-cv-tim for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (unispeech-large-1500h-cv-tim below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -F model="unispeech-large-1500h-cv-tim" -F file=@audio.mp3

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Sizes, precisions & builds

unispeech-large-1500h-cv-timit

— · BF16

Weights ↗

Details

Trained / evaluated on

timit_asr