metadata
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-v0.7
results: []
nb-whisper-large-v0.7
This model is a fine-tuned version of 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: 0.4299
- train_loss: 0.4933
- validation_nst_wer: 2.1830
- validation_nst_cer: 0.6702
- validation_nst_exact_wer: 2.7220
- validation_nst_exact_cer: 0.7519
- validation_clean_stortinget_no_loss: 0.7253
- validation_clean_stortinget_no_wer: 8.9886
- validation_clean_stortinget_no_cer: 5.7594
- validation_clean_stortinget_no_exact_wer: 11.8515
- validation_clean_stortinget_no_exact_cer: 6.2132
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: 7798
- 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 | 0.4271 | 0.9562 | 2.1721 | 0.6246 | 2.7056 | 0.7070 | 0.6866 | 8.5836 | 5.4517 | 11.4126 | 5.8853 |
| 5000 | 0.4400 | 0.5815 | 2.6621 | 0.7765 | 3.1629 | 0.8526 | 0.7085 | 9.1000 | 5.7626 | 12.1172 | 6.2354 |
| 10000 | 0.4377 | 0.5548 | 2.2701 | 0.6740 | 2.9016 | 0.7720 | 0.6845 | 9.2823 | 5.9461 | 12.1717 | 6.4073 |
| 15000 | 0.4332 | 0.5112 | 2.3246 | 0.6917 | 2.8799 | 0.7775 | 0.7101 | 9.1307 | 5.8030 | 11.9654 | 6.2408 |
| 20000 | 0.4345 | 0.5066 | 2.3518 | 0.7122 | 2.8962 | 0.7940 | 0.7083 | 9.0668 | 5.8133 | 11.9867 | 6.2755 |
| 25000 | 0.4315 | 0.4955 | 2.2266 | 0.6740 | 2.7873 | 0.7601 | 0.7034 | 9.0313 | 5.7971 | 11.9535 | 6.2588 |
| 30000 | 0.4332 | 0.4936 | 2.2429 | 0.6936 | 2.7764 | 0.7757 | 0.7110 | 8.9957 | 5.7534 | 11.8230 | 6.1968 |
| 35000 | 0.4311 | 0.4947 | 2.2102 | 0.6777 | 2.7438 | 0.7592 | 0.7138 | 9.0076 | 5.7879 | 11.8752 | 6.2463 |
| 40000 | 0.4305 | 0.5026 | 2.2048 | 0.6805 | 2.7492 | 0.7638 | 0.7259 | 8.9152 | 5.6809 | 11.7827 | 6.1356 |
| 45000 | 0.4309 | 0.4815 | 2.1612 | 0.6572 | 2.7111 | 0.7436 | 0.7293 | 9.0265 | 5.7800 | 11.9179 | 6.2404 |
| 49999 | 0.4299 | 0.4933 | 2.1830 | 0.6702 | 2.7220 | 0.7519 | |||||
| 49999 | 0.7253 | 0.4933 | 8.9886 | 5.7594 | 11.8515 | 6.2132 |
Framework versions
- Transformers 4.35.2
- Datasets 2.15.0
- Tokenizers 0.14.1