whisper-small-smj-test

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whisper-small-smj

This model is a fine-tuned version of openai/whisper-small on the NbAiLab/salmon-asr-smj dataset. It achieves the following results on the evaluation set:

• step: 9999
• validation_loss: 0.3690
• train_loss: 0.2159
• validation_wer: 19.6809
• validation_cer: 5.5037
• validation_exact_wer: 22.3404
• validation_exact_cer: 5.8753

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: 5e-05
• lr_scheduler_type: linear
• per_device_train_batch_size: 32
• total_train_batch_size_per_node: 256
• total_train_batch_size: 256
• total_optimization_steps: 10,000
• starting_optimization_step: None
• finishing_optimization_step: 10,000
• num_train_dataset_workers: 32
• num_hosts: 1
• total_num_training_examples: 2,560,000
• steps_per_epoch: 70
• num_beams: None
• weight_decay: 0.01
• adam_beta1: 0.9
• adam_beta2: 0.98
• adam_epsilon: 1e-06
• dropout: True
• bpe_dropout_probability: 0.2
• activation_dropout_probability: 0.1

Training results

Framework versions

• Transformers 4.34.1
• Datasets 2.14.5
• Tokenizers 0.14.1