transformers jax tensorboard whisper automatic-speech-recognition audio asr hf-asr-leaderboard no base_model:NbAiLab/nb-whisper-large-v3-RC4 license:apache-2.0 endpoints_compatible region:us
---
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
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# nb-whisper-large-v0.8

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 dataset.
It achieves the following results on the evaluation set:
- step: 49999
- validation_nst_loss: 0.4309
- train_loss: 0.4828
- validation_nst_wer: 2.2211
- validation_nst_cer: 0.6758
- validation_nst_exact_wer: 2.7655
- validation_nst_exact_cer: 0.7592
- validation_clean_stortinget_no_loss: 0.7845
- validation_clean_stortinget_no_wer: 8.8323
- validation_clean_stortinget_no_cer: 5.6753
- validation_clean_stortinget_no_exact_wer: 11.6973
- validation_clean_stortinget_no_exact_cer: 6.1161

## 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: 50,000
- starting_optimization_step: None
- finishing_optimization_step: 50,000
- num_train_dataset_workers: 32
- num_hosts: 32
- total_num_training_examples: 51,200,000
- steps_per_epoch: 7254
- 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     | 0.4265              | 0.9701     | 2.1721             | 0.6246             | 2.7056                   | 0.7070                   | 0.6866                              | 8.5836                             | 5.4517                             | 11.4126                                  | 5.8853                                   |
| 5000  | 0.4380              | 0.6065     | 2.5750             | 0.7495             | 3.0922                   | 0.8251                   | 0.6988                              | 9.1284                             | 5.8272                             | 12.0840                                  | 6.2946                                   |
| 10000 | 0.4366              | 0.5640     | 2.3191             | 0.6852             | 2.8417                   | 0.7647                   | 0.7061                              | 9.1378                             | 5.7729                             | 12.0270                                  | 6.2225                                   |
| 15000 | 0.4370              | 0.5506     | 2.3300             | 0.7066             | 2.9234                   | 0.7976                   | 0.7213                              | 8.9673                             | 5.6884                             | 11.9511                                  | 6.1640                                   |
| 20000 | 0.4328              | 0.5284     | 2.3300             | 0.7019             | 2.8962                   | 0.7885                   | 0.7674                              | 8.8915                             | 5.6535                             | 11.7922                                  | 6.1013                                   |
| 25000 | 0.4334              | 0.5133     | 2.3082             | 0.7010             | 2.9016                   | 0.7903                   | 0.7697                              | 9.0194                             | 5.7983                             | 11.8468                                  | 6.2373                                   |
| 30000 | 0.4301              | 0.4996     | 2.1721             | 0.6674             | 2.6948                   | 0.7464                   | 0.7732                              | 8.9223                             | 5.7229                             | 11.8349                                  | 6.1726                                   |
| 35000 | 0.4310              | 0.4957     | 2.2592             | 0.6926             | 2.8472                   | 0.7830                   | 0.7882                              | 8.9744                             | 5.7804                             | 11.8871                                  | 6.2323                                   |
| 40000 | 0.4301              | 0.4999     | 2.1939             | 0.6647             | 2.7165                   | 0.7436                   | 0.7899                              | 8.8868                             | 5.6412                             | 11.7708                                  | 6.0880                                   |
| 45000 | 0.4306              | 0.5049     | 2.2320             | 0.6768             | 2.7819                   | 0.7628                   | 0.7766                              | 8.8252                             | 5.6686                             | 11.6902                                  | 6.1087                                   |
| 49999 | 0.4309              | 0.4828     | 2.2211             | 0.6758             | 2.7655                   | 0.7592                   |
| 49999 | 0.7845              | 0.4828     | 8.8323             | 5.6753             | 11.6973                  | 6.1161                   |


### Framework versions

- Transformers 4.36.2
- Datasets 2.16.0
- Tokenizers 0.15.0
