cahya / whisper-medium-id

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7-day runs: 588
30-day runs: 961
Model's Last Updated: May 22 2024
automatic-speech-recognition

Introduction of whisper-medium-id

Model Details of whisper-medium-id

Whisper Medium Indonesian

This model is a fine-tuned version of openai/whisper-medium on the Indonesian mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset. It achieves the following results:

CV11 test split:
  • Loss: 0.0698
  • Wer: 3.8274
Google/fleurs test split:
  • Wer: 9.74
Usage
from transformers import pipeline
transcriber = pipeline(
  "automatic-speech-recognition", 
  model="cahya/whisper-medium-id"
)
transcriber.model.config.forced_decoder_ids = (
  transcriber.tokenizer.get_decoder_prompt_ids(
    language="id" 
    task="transcribe"
  )
)
transcription = transcriber("my_audio_file.mp3")
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-06
  • 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: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer
0.0427 0.33 1000 0.0664 4.3807
0.042 0.66 2000 0.0658 3.9426
0.0265 0.99 3000 0.0657 3.8274
0.0211 1.32 4000 0.0679 3.8366
0.0212 1.66 5000 0.0682 3.8412
0.0206 1.99 6000 0.0683 3.8689
0.0166 2.32 7000 0.0711 3.9657
0.0095 2.65 8000 0.0717 3.9980
0.0122 2.98 9000 0.0714 3.9795
0.0049 3.31 10000 0.0720 3.9887
Evaluation

We evaluated the model using the test split of two datasets, the Common Voice 11 and the Google Fleurs . As Whisper can transcribe casing and punctuation, we also evaluate its performance using raw and normalized text. (lowercase + removal of punctuations). The results are as follows:

Common Voice 11
Google/Fleurs
Framework versions
  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2

Runs of cahya whisper-medium-id on huggingface.co

1.2K
Total runs
6
24-hour runs
10
3-day runs
588
7-day runs
961
30-day runs

More Information About whisper-medium-id huggingface.co Model

More whisper-medium-id license Visit here:

https://choosealicense.com/licenses/apache-2.0

whisper-medium-id huggingface.co

whisper-medium-id huggingface.co is an AI model on huggingface.co that provides whisper-medium-id's model effect (), which can be used instantly with this cahya whisper-medium-id model. huggingface.co supports a free trial of the whisper-medium-id model, and also provides paid use of the whisper-medium-id. Support call whisper-medium-id model through api, including Node.js, Python, http.

whisper-medium-id huggingface.co Url

https://huggingface.co/cahya/whisper-medium-id

cahya whisper-medium-id online free

whisper-medium-id huggingface.co is an online trial and call api platform, which integrates whisper-medium-id's modeling effects, including api services, and provides a free online trial of whisper-medium-id, you can try whisper-medium-id online for free by clicking the link below.

cahya whisper-medium-id online free url in huggingface.co:

https://huggingface.co/cahya/whisper-medium-id

whisper-medium-id install

whisper-medium-id is an open source model from GitHub that offers a free installation service, and any user can find whisper-medium-id on GitHub to install. At the same time, huggingface.co provides the effect of whisper-medium-id install, users can directly use whisper-medium-id installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

whisper-medium-id install url in huggingface.co:

https://huggingface.co/cahya/whisper-medium-id

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whisper-medium-id huggingface.co Url

Provider of whisper-medium-id huggingface.co

cahya
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