---
language:
- 'no'
license: apache-2.0
base_model: NbAiLab/nb-whisper-base-RC1
tags:
- audio
- asr
- automatic-speech-recognition
- hf-asr-leaderboard
model-index:
- name: nb-whisper-base-v0.8-vad3
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# nb-whisper-base-v0.8-vad3

This model is a fine-tuned version of [NbAiLab/nb-whisper-base-RC1](https://huggingface.co/NbAiLab/nb-whisper-base-RC1) on the NbAiLab/ncc_speech_styling_v2_vad3 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: 0.0001
- lr_scheduler_type: linear
- per_device_train_batch_size: 32
- total_train_batch_size_per_node: 128
- total_train_batch_size: 1024
- total_optimization_steps: 50,000
- starting_optimization_step: None
- finishing_optimization_step: 50,000
- num_train_dataset_workers: 32
- num_hosts: 8
- total_num_training_examples: 51,200,000
- steps_per_epoch: 7455
- 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

| step  | validation_nst_loss | train_loss | validation_nst_wer | validation_nst_cer | validation_nst_exact_wer | validation_nst_exact_cer | validation_clean_stortinget_no_loss | validation_clean_stortinget_no_wer | validation_clean_stortinget_no_cer | validation_clean_stortinget_no_exact_wer | validation_clean_stortinget_no_exact_cer |
|:-----:|:-------------------:|:----------:|:------------------:|:------------------:|:------------------------:|:------------------------:|:-----------------------------------:|:----------------------------------:|:----------------------------------:|:----------------------------------------:|:----------------------------------------:|
| 0     | 0.4594              | 1.1239     | 4.7580             | 1.4524             | 5.4984                   | 1.5715                   | 0.5892                              | 11.7267                            | 6.8997                             | 15.1963                                  | 7.4616                                   |
| 5000  | 0.4884              | 0.6674     | 5.5038             | 1.7824             | 6.2987                   | 1.9002                   | 0.6483                              | 13.0246                            | 7.4564                             | 16.7240                                  | 8.0698                                   |
| 10000 | 0.4834              | 0.6476     | 5.5474             | 1.8085             | 6.2823                   | 1.9149                   | 0.6467                              | 12.9252                            | 7.4203                             | 16.4844                                  | 8.0062                                   |
| 15000 | 0.4843              | 0.6350     | 5.6672             | 1.7963             | 6.4456                   | 1.9222                   | 0.6517                              | 12.7144                            | 7.3438                             | 16.2709                                  | 7.9357                                   |
| 20000 | 0.4760              | 0.5842     | 5.1010             | 1.6146             | 5.8033                   | 1.7244                   | 0.6517                              | 12.6338                            | 7.3208                             | 16.2780                                  | 7.9279                                   |
| 25000 | 0.4806              | 0.5751     | 5.1718             | 1.6323             | 5.8849                   | 1.7354                   | 0.6512                              | 12.6078                            | 7.2514                             | 16.1713                                  | 7.8452                                   |
| 30000 | 0.4740              | 0.5723     | 4.7090             | 1.4878             | 5.4058                   | 1.6035                   | 0.6482                              | 12.4917                            | 7.2427                             | 16.0337                                  | 7.8222                                   |
| 35000 | 0.4737              | 0.5598     | 4.8887             | 1.5241             | 5.7216                   | 1.6548                   | 0.6510                              | 12.2572                            | 7.0924                             | 15.7917                                  | 7.6744                                   |
| 40000 | 0.4731              | 0.5471     | 4.8941             | 1.5297             | 5.6073                   | 1.6438                   | 0.6526                              | 12.4064                            | 7.1642                             | 15.8842                                  | 7.7360                                   |
| 45000 | 0.4693              | 0.5217     | 4.7580             | 1.4645             | 5.4930                   | 1.5834                   | 0.6471                              | 12.1696                            | 7.0908                             | 15.7134                                  | 7.6776                                   |


### Framework versions

- Transformers 4.34.1
- Datasets 2.16.1
- Tokenizers 0.14.1