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

This model is a fine-tuned version of [NbAiLab/nb-whisper-small-RC1](https://huggingface.co/NbAiLab/nb-whisper-small-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: 5e-05
- 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     | 0.4313              | 1.0396     | 2.8254             | 0.8865             | 3.5168                   | 0.9900                   | 0.5547                              | 9.6092                             | 5.9949                             | 12.6794                                  | 6.4755                                   |
| 5000  | 0.4484              | 0.5692     | 3.2010             | 1.0142             | 3.8870                   | 1.1172                   | 0.6138                              | 10.1824                            | 6.1896                             | 13.4124                                  | 6.6954                                   |
| 10000 | 0.4477              | 0.5317     | 3.3589             | 1.0347             | 4.0176                   | 1.1337                   | 0.6275                              | 10.3316                            | 6.4310                             | 13.6022                                  | 6.9442                                   |
| 15000 | 0.4493              | 0.5132     | 3.3099             | 1.0086             | 3.9904                   | 1.1145                   | 0.6599                              | 10.2203                            | 6.3042                             | 13.4100                                  | 6.8175                                   |
| 20000 | 0.4491              | 0.4911     | 3.2283             | 1.0226             | 3.8924                   | 1.1227                   | 0.6755                              | 10.1421                            | 6.3188                             | 13.4409                                  | 6.8428                                   |
| 25000 | 0.4441              | 0.4766     | 3.1575             | 0.9816             | 3.8924                   | 1.0898                   | 0.6763                              | 10.2700                            | 6.3383                             | 13.5951                                  | 6.8658                                   |
| 30000 | 0.4498              | 0.4632     | 3.1357             | 0.9741             | 3.8543                   | 1.0797                   | 0.6599                              | 10.2274                            | 6.3787                             | 13.5144                                  | 6.8974                                   |


### Framework versions

- Transformers 4.34.1
- Datasets 2.16.1
- Tokenizers 0.14.1