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zuazo
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whisper-large-v2-eu-from-es

Automatic Speech Recognition
Transformers
PyTorch
Basque
whisper
whisper-event
Generated from Trainer
Eval Results
Inference Endpoints
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whisper-large-v2-eu-from-es / README.md
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metadata
language:
  - eu
license: apache-2.0
base_model: zuazo/whisper-large-v2-es
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Large-V2 Basque
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0 eu
          type: mozilla-foundation/common_voice_13_0
          config: eu
          split: test
          args: eu
        metrics:
          - name: Wer
            type: wer
            value: 11.839280651302198

Whisper Large-V2 Basque

This model is a fine-tuned version of zuazo/whisper-large-v2-es on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4245
  • Wer: 11.8393

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 20000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0293 4.01 1000 0.2732 15.9484
0.0065 9.01 2000 0.3051 14.1136
0.0033 14.01 3000 0.3101 13.2407
0.0041 19.0 4000 0.3136 13.8300
0.0013 24.0 5000 0.3179 12.7364
0.0046 29.0 6000 0.3210 13.6640
0.0015 33.01 7000 0.3262 12.8093
0.0027 38.01 8000 0.3210 12.9612
0.0005 43.01 9000 0.3376 12.7850
0.0007 48.01 10000 0.3361 12.9126
0.0002 53.0 11000 0.3559 12.3739
0.0001 58.0 12000 0.3550 12.3355
0.0 63.0 13000 0.3852 12.1147
0.0 67.01 14000 0.3974 12.0134
0.0 72.01 15000 0.4072 11.9446
0.0 77.01 16000 0.4162 11.9203
0.0 82.01 17000 0.4245 11.8393
0.0 87.0 18000 0.4319 11.8616
0.0 92.0 19000 0.4375 11.8535
0.0 97.0 20000 0.4400 11.8656

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3