metadata

language:
  - he
license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - ivrit-ai/whisper-training
metrics:
  - wer
model-index:
  - name: Whisper Small Hebrew
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ivrit-ai/whisper-training
          type: ivrit-ai/whisper-training
          args: 'config: he, split: train'
        metrics:
          - name: Wer
            type: wer
            value: 37.8652

Whisper Small Hebrew

This model is a fine-tuned version of openai/whisper-small on the ivrit-ai/whisper-training dataset.

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: 16
eval_batch_size: 8
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

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1
Datasets 2.18.0
Tokenizers 0.15.2