---
language:
- 'no'
license: apache-2.0
base_model: NbAiLab/nb-whisper-large-v3-RC4
tags:
- audio
- asr
- automatic-speech-recognition
- hf-asr-leaderboard
model-index:
- name: nb-whisper-large-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-large-v0.8-vad3

This model is a fine-tuned version of [NbAiLab/nb-whisper-large-v3-RC4](https://huggingface.co/NbAiLab/nb-whisper-large-v3-RC4) 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: 7e-05
- lr_scheduler_type: linear
- per_device_train_batch_size: 8
- total_train_batch_size_per_node: 32
- total_train_batch_size: 1024
- total_optimization_steps: 15,000
- starting_optimization_step: 35,000
- finishing_optimization_step: 50,000
- num_train_dataset_workers: 32
- num_hosts: 32
- total_num_training_examples: 51,200,000
- steps_per_epoch: _To be computed after first epoch_
- 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     | 0.4259              | 0.9588     | 2.1721             | 0.6246             | 2.7111                   | 0.7079                   | 0.6807                              | 8.5931                             | 5.4608                             | 11.4221                                  | 5.8946                                   |
| 5000  | 0.4376              | 0.5822     | 2.5859             | 0.7793             | 3.0867                   | 0.8563                   | 0.6738                              | 9.1686                             | 5.8478                             | 12.0792                                  | 6.3020                                   |
| 10000 | 0.4368              | 0.5675     | 2.5913             | 0.7271             | 3.2337                   | 0.8269                   | 0.6875                              | 9.2705                             | 5.9200                             | 12.1741                                  | 6.3750                                   |
| 15000 | 0.4335              | 0.5403     | 2.3409             | 0.6936             | 2.9180                   | 0.7821                   | 0.7187                              | 9.0834                             | 5.7344                             | 11.9962                                  | 6.1944                                   |
| 20000 | 0.4324              | 0.5187     | 2.3518             | 0.6945             | 2.9561                   | 0.7857                   | 0.7357                              | 8.9839                             | 5.7154                             | 11.8610                                  | 6.1664                                   |
| 25000 | 0.4307              | 0.5158     | 2.3028             | 0.6712             | 2.9343                   | 0.7711                   | 0.7228                              | 9.1284                             | 5.8704                             | 11.9915                                  | 6.3161                                   |
| 30000 | 0.4312              | 0.5108     | 2.2810             | 0.6656             | 2.8690                   | 0.7564                   | 0.7428                              | 8.9010                             | 5.6726                             | 11.8349                                  | 6.1305                                   |
| 35000 | 0.4299              | 0.4908     | 2.2320             | 0.6768             | 2.8417                   | 0.7729                   | 0.7513                              | 8.8015                             | 5.6123                             | 11.6854                                  | 6.0642                                   |


### Framework versions

- Transformers 4.36.2
- Datasets 2.16.1
- Tokenizers 0.15.0