whisper_tiny_cs / README.md
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metadata
language:
  - cs
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper tiny Czech CV13 v1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0 cs
          type: mozilla-foundation/common_voice_13_0
          config: cs
          split: test
          args: cs
        metrics:
          - name: Wer
            type: wer
            value: 44.080171349061175

Whisper tiny Czech CV13 v1

This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_13_0 cs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5430
  • Wer: 44.0802

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
  • distributed_type: multi-GPU
  • num_devices: 3
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 384
  • total_eval_batch_size: 48
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • training_steps: 3000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1007 21.86 1000 0.5430 44.0802
0.013 43.72 2000 0.6489 44.9182
0.0079 65.57 3000 0.6782 45.5169

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3