Model reference · open weights

whisper-medium-jp

Available as managed deployment Audio vumichien · community Speech→text 1 variants 10k dl/mo

whisper-medium-jp is an open-weight audio or speech model from vumichien. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

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

What it is

Released byvumichien
TypeAudio & music
TaskSpeech→text
Runs withtransformers
Released2022-12-07
Popularity10k downloads / month
LicenceOpen weights

About

What whisper-medium-jp is

This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3029
  • Wer: 9.0355
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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.03923.0310000.202310.1807
0.00367.0120000.24789.4409
0.001310.0430000.27919.1014
0.000214.0140000.29709.0625
0.000217.0450000.30299.0355

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2

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

Benchmarks

Reported results

As published on the model card — the maker's own numbers, not measured by AxForge.

TaskDatasetMetricScore
Automatic Speech Recognitionmozilla-foundation/common_voice_11_0 jaWER9.035
Automatic Speech Recognitionmozilla-foundation/common_voice_11_0 jaCER5.610
Automatic Speech Recognitiongoogle/fleurs ja_jpWER13.560
Automatic Speech Recognitiongoogle/fleurs ja_jpCER8.010

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys whisper-medium-jp for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (whisper-medium-jp 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="whisper-medium-jp" -F file=@audio.mp3

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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