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zuazo
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whisper-large-eu-from-es

Automatic Speech Recognition
Transformers
PyTorch
Basque
whisper
whisper-event
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
whisper-large-eu-from-es / README.md
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metadata
language:
  - eu
license: apache-2.0
base_model: zuazo/whisper-large-es
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Large 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: 12.981489732269432

Whisper Large Basque

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

  • Loss: 0.4549
  • Wer: 12.9815

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
0.0162 4.01 1000 0.3159 16.8577
0.0042 9.01 2000 0.3181 15.1606
0.0038 14.01 3000 0.3367 14.7211
0.0035 19.0 4000 0.3419 14.5915
0.0012 24.0 5000 0.3489 14.3586
0.0029 29.0 6000 0.3650 14.6746
0.0011 33.01 7000 0.3643 13.8138
0.0006 38.01 8000 0.3628 14.0042
0.0009 43.01 9000 0.3661 14.0042
0.0003 48.01 10000 0.3794 13.7166
0.0003 53.0 11000 0.3793 13.6923
0.0 58.0 12000 0.3991 13.4027
0.0 63.0 13000 0.4119 13.3562
0.0 67.01 14000 0.4209 13.2184
0.0 72.01 15000 0.4288 13.2225
0.0 77.01 16000 0.4361 13.1516
0.0 82.01 17000 0.4428 13.1334
0.0 87.0 18000 0.4487 13.1334
0.0 92.0 19000 0.4531 12.9896
0.0 97.0 20000 0.4549 12.9815

Framework versions

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