---
base_model: NbAiLab/nb-whisper-small-verbatim
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: nb-whisper-small-karelian-CodeSwitching
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# nb-whisper-small-karelian-CodeSwitching

This model is a fine-tuned version of [NbAiLab/nb-whisper-small-verbatim](https://huggingface.co/NbAiLab/nb-whisper-small-verbatim) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7241
- Wer: 0.3278
- Cer: 0.0999

## 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
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 0.1848        | 1.1338  | 500   | 0.6758          | 0.4066 | 0.1227 |
| 0.0796        | 2.2676  | 1000  | 0.6685          | 0.3549 | 0.1015 |
| 0.0492        | 3.4014  | 1500  | 0.7090          | 0.3758 | 0.1088 |
| 0.0426        | 4.5351  | 2000  | 0.7095          | 0.3704 | 0.1083 |
| 0.0311        | 5.6689  | 2500  | 0.7148          | 0.3742 | 0.1138 |
| 0.027         | 6.8027  | 3000  | 0.7173          | 0.3454 | 0.1004 |
| 0.0201        | 7.9365  | 3500  | 0.7261          | 0.3813 | 0.1325 |
| 0.0165        | 9.0703  | 4000  | 0.7158          | 0.3417 | 0.0982 |
| 0.0179        | 10.2041 | 4500  | 0.7261          | 0.3495 | 0.1036 |
| 0.0101        | 11.3379 | 5000  | 0.7275          | 0.3315 | 0.0978 |
| 0.0086        | 12.4717 | 5500  | 0.7437          | 0.3400 | 0.1081 |
| 0.0058        | 13.6054 | 6000  | 0.7524          | 0.3410 | 0.1026 |
| 0.0056        | 14.7392 | 6500  | 0.7256          | 0.3407 | 0.1015 |
| 0.0075        | 15.8730 | 7000  | 0.7202          | 0.3312 | 0.0987 |
| 0.0047        | 17.0068 | 7500  | 0.7266          | 0.3359 | 0.1025 |
| 0.0046        | 18.1406 | 8000  | 0.7271          | 0.3312 | 0.0973 |
| 0.0039        | 19.2744 | 8500  | 0.7334          | 0.3353 | 0.0999 |
| 0.0025        | 20.4082 | 9000  | 0.7280          | 0.3295 | 0.0987 |
| 0.0022        | 21.5420 | 9500  | 0.7290          | 0.3254 | 0.0972 |
| 0.0031        | 22.6757 | 10000 | 0.7241          | 0.3278 | 0.0999 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1