README.md

metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - NbAiLab/NCC_S
metrics:
  - wer
model-index:
  - name: Whisper Base Norwegian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: NbAiLab/NCC_S
          type: NbAiLab/NCC_S
          config: 'no'
          split: validation
          args: 'no'
        metrics:
          - name: Wer
            type: wer
            value: 15.012180267965894

Whisper Base Norwegian

This model is a fine-tuned version of pere/whisper-small-nob-clr on the NbAiLab/NCC_S dataset. It achieves the following results on the evaluation set:

• Loss: 0.3284
• Wer: 15.0122

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: 64
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• training_steps: 3000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5975	0.33	1000	0.3354	15.7734
0.5783	0.67	2000	0.3327	16.3520
0.5788	1.0	3000	0.3284	15.0122

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2