Hugging Face's logo

marinone94
/
whisper-medium-nordic

Automatic Speech Recognition
Transformers
PyTorch
5 datasets
4 languages
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results
Inference Endpoints
Model card Files Community
3
whisper-medium-nordic / README.md
marinone94's picture
marinone94
push training
da9f196
preview code
|
raw
history blame
No virus
3.76 kB
metadata
language:
  - sv
  - 'no'
  - da
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
  - mozilla-foundation/common_voice_11_0
  - mozilla-foundation/common_voice_11_0
  - babelbox/babelbox_voice
  - NbAiLab/NST
  - NbAiLab/NPSC
  - google/fleurs
  - google/fleurs
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper Medium Nordic
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: sv-SE
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 11.307923879152778
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: babelbox/babelbox_voice
          type: babelbox/babelbox_voice
        metrics:
          - name: Wer
            type: wer
            value: 11.307923879152778
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: NbAiLab/NST
          type: NbAiLab/NST
        metrics:
          - name: Wer
            type: wer
            value: 11.307923879152778
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: NbAiLab/NPSC
          type: NbAiLab/NPSC
        metrics:
          - name: Wer
            type: wer
            value: 11.307923879152778
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
        metrics:
          - name: Wer
            type: wer
            value: 11.307923879152778

Whisper Medium Nordic

This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0, the mozilla-foundation/common_voice_11_0, the mozilla-foundation/common_voice_11_0, the babelbox/babelbox_voice, the NbAiLab/NST, the NbAiLab/NPSC, the google/fleurs, the google/fleurs and the google/fleurs datasets. It achieves the following results on the evaluation set:

  • Loss: 0.2129
  • Wer: 11.3079

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: 3e-06
  • 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_ratio: 0.1
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3056 0.1 1000 0.2670 99.9221
0.16 0.2 2000 0.2322 99.6640
0.1309 0.3 3000 0.2152 98.9759
0.097 0.4 4000 0.2112 100.0
0.091 0.5 5000 0.2094 99.7312
0.1098 0.6 6000 0.2098 98.6077
0.0637 0.7 7000 0.2148 98.4625
0.0718 0.8 8000 0.2151 99.8710
0.0517 0.9 9000 0.2175 97.2342
0.0465 1.0 10000 0.2129 96.3552

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2