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---
language:
- 'no'
license: apache-2.0
base_model: NbAiLab/nb-whisper-medium-v0.8-vad3
tags:
- audio
- asr
- automatic-speech-recognition
- hf-asr-leaderboard
model-index:
- name: nb-whisper-medium-v0.8-vad3-verbatim
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-medium-v0.8-vad3-verbatim
This model is a fine-tuned version of [NbAiLab/nb-whisper-medium-v0.8-vad3](https://huggingface.co/NbAiLab/nb-whisper-medium-v0.8-vad3) on the NbAiLab/NPSC dataset.
It achieves the following results on the evaluation set:
- step: 249
- validation_loss: 0.6296
- train_loss: 0.4324
- validation_wer: 8.2769
- validation_cer: 2.8193
- validation_exact_wer: 8.4048
- validation_exact_cer: 2.8363
## 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: 2.5e-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: 250
- starting_optimization_step: None
- finishing_optimization_step: 250
- num_train_dataset_workers: 32
- num_hosts: 8
- total_num_training_examples: 256,000
- steps_per_epoch: 45
- 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_loss | train_loss | validation_wer | validation_cer | validation_exact_wer | validation_exact_cer |
|:----:|:---------------:|:----------:|:--------------:|:--------------:|:--------------------:|:--------------------:|
| 0 | 1.5895 | 1.4606 | 17.5605 | 10.5650 | 33.0099 | 13.8415 |
| 40 | 0.6409 | 0.5035 | 9.1662 | 3.0250 | 9.3637 | 3.0542 |
| 80 | 0.6309 | 0.4790 | 8.7132 | 2.9755 | 8.8730 | 2.9952 |
| 120 | 0.6250 | 0.4480 | 8.4503 | 2.8812 | 8.6079 | 2.9019 |
| 160 | 0.6294 | 0.4423 | 8.4000 | 2.8641 | 8.5345 | 2.8810 |
| 200 | 0.6276 | 0.4467 | 8.3161 | 2.8345 | 8.4668 | 2.8534 |
| 240 | 0.6287 | 0.4376 | 8.2266 | 2.7917 | 8.3597 | 2.8087 |
| 249 | 0.6296 | 0.4324 | 8.2769 | 2.8193 | 8.4048 | 2.8363 |
### Framework versions
- Transformers 4.34.1
- Datasets 2.16.1
- Tokenizers 0.14.1
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