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

This model is a fine-tuned version of [NbAiLab/nb-whisper-tiny-RC1](https://huggingface.co/NbAiLab/nb-whisper-tiny-RC1) on the NbAiLab/ncc_speech_styling_v2_vad3 dataset.
It achieves the following results on the evaluation set:
- step: 49999
- validation_nst_loss: 0.5107
- train_loss: 0.6596
- validation_nst_wer: 7.8121
- validation_nst_cer: 2.4815
- validation_nst_exact_wer: 8.6559
- validation_nst_exact_cer: 2.6081
- validation_clean_stortinget_no_loss: 0.7180
- validation_clean_stortinget_no_wer: 16.0137
- validation_clean_stortinget_no_cer: 8.6585
- validation_clean_stortinget_no_exact_wer: 19.8672
- validation_clean_stortinget_no_exact_cer: 9.3568

## 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: 0.00015
- 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     | 0.5115              | 1.2809     | 7.9808             | 2.5868             | 8.9172                   | 2.7299                   | 0.6754                              | 16.0516                            | 8.8512                             | 19.8245                                  | 9.5377                                   |
| 5000  | 0.5513              | 0.7948     | 9.8699             | 3.1480             | 10.7083                  | 3.2666                   | 0.8315                              | 18.2473                            | 9.7512                             | 22.3081                                  | 10.4913                                  |
| 10000 | 0.5434              | 0.7729     | 9.5433             | 3.0613             | 10.3490                  | 3.1851                   | 0.7654                              | 17.9536                            | 9.6422                             | 21.9855                                  | 10.3974                                  |
| 15000 | 0.5380              | 0.7629     | 9.0914             | 2.9523             | 9.9243                   | 3.0779                   | 0.7651                              | 17.6694                            | 9.2759                             | 21.5443                                  | 9.9923                                   |
| 20000 | 0.5364              | 0.7173     | 8.7974             | 2.8684             | 9.6412                   | 2.9882                   | 0.7469                              | 17.0725                            | 9.1391                             | 20.9963                                  | 9.8515                                   |
| 25000 | 0.5311              | 0.7168     | 8.6559             | 2.7453             | 9.5160                   | 2.8700                   | 0.7347                              | 16.8167                            | 9.0130                             | 20.7615                                  | 9.7248                                   |
| 30000 | 0.5282              | 0.6977     | 8.4545             | 2.7090             | 9.2711                   | 2.8362                   | 0.7588                              | 16.5632                            | 8.9523                             | 20.4650                                  | 9.6476                                   |
| 35000 | 0.5232              | 0.6851     | 8.4000             | 2.7062             | 9.2547                   | 2.8316                   | 0.7314                              | 16.2577                            | 8.7608                             | 20.2135                                  | 9.4749                                   |
| 40000 | 0.5215              | 0.6878     | 8.3238             | 2.6251             | 9.1676                   | 2.7528                   | 0.7387                              | 16.3098                            | 8.8231                             | 20.1542                                  | 9.5131                                   |
| 45000 | 0.5156              | 0.6901     | 7.9264             | 2.5309             | 8.7158                   | 2.6466                   | 0.7236                              | 16.1037                            | 8.8698                             | 19.9620                                  | 9.5607                                   |
| 49999 | 0.5107              | 0.6596     | 7.8121             | 2.4815             | 8.6559                   | 2.6081                   |
| 49999 | 0.7180              | 0.6596     | 16.0137            | 8.6585             | 19.8672                  | 9.3568                   |


### Framework versions

- Transformers 4.34.1
- Datasets 2.16.1
- Tokenizers 0.14.1