---
license: apache-2.0
base_model: NbAiLab/nb-whisper-large
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: whisper-large-no-fo-100h-30k-steps
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ravnursson_asr
      type: ravnursson_asr
      config: ravnursson_asr
      split: test
      args: ravnursson_asr
    metrics:
    - name: Wer
      type: wer
      value: 4.066841151600563
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/setur/huggingface/runs/apivajor)
# whisper-large-no-fo-100h-30k-steps

This model is a fine-tuned version of [NbAiLab/nb-whisper-large](https://huggingface.co/NbAiLab/nb-whisper-large) on the ravnursson_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0743
- Wer: 4.0668

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 30000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2496        | 0.2320 | 1000  | 0.2656          | 19.1061 |
| 0.162         | 0.4640 | 2000  | 0.1777          | 13.0914 |
| 0.1308        | 0.6961 | 3000  | 0.1410          | 10.9573 |
| 0.1272        | 0.9281 | 4000  | 0.1217          | 9.6889  |
| 0.0629        | 1.1601 | 5000  | 0.1131          | 8.5263  |
| 0.0636        | 1.3921 | 6000  | 0.1089          | 8.4004  |
| 0.053         | 1.6241 | 7000  | 0.1026          | 7.3384  |
| 0.0528        | 1.8561 | 8000  | 0.0911          | 6.9609  |
| 0.0232        | 2.0882 | 9000  | 0.0963          | 6.9307  |
| 0.0218        | 2.3202 | 10000 | 0.0936          | 6.6841  |
| 0.0241        | 2.5522 | 11000 | 0.0868          | 6.4526  |
| 0.0326        | 2.7842 | 12000 | 0.0866          | 6.5331  |
| 0.0136        | 3.0162 | 13000 | 0.0820          | 5.6020  |
| 0.0098        | 3.2483 | 14000 | 0.0822          | 5.5969  |
| 0.0116        | 3.4803 | 15000 | 0.0806          | 5.4812  |
| 0.0117        | 3.7123 | 16000 | 0.0811          | 5.4963  |
| 0.013         | 3.9443 | 17000 | 0.0792          | 5.3704  |
| 0.0042        | 4.1763 | 18000 | 0.0778          | 4.8722  |
| 0.0078        | 4.4084 | 19000 | 0.0795          | 4.8822  |
| 0.0078        | 4.6404 | 20000 | 0.0785          | 4.7010  |
| 0.0076        | 4.8724 | 21000 | 0.0763          | 4.7061  |
| 0.0042        | 5.1044 | 22000 | 0.0753          | 4.5098  |
| 0.0037        | 5.3364 | 23000 | 0.0765          | 4.5400  |
| 0.0027        | 5.5684 | 24000 | 0.0757          | 4.4041  |
| 0.0037        | 5.8005 | 25000 | 0.0745          | 4.4242  |
| 0.0012        | 6.0325 | 26000 | 0.0742          | 4.3336  |
| 0.0006        | 6.2645 | 27000 | 0.0744          | 4.1675  |
| 0.0009        | 6.4965 | 28000 | 0.0760          | 4.1574  |
| 0.0006        | 6.7285 | 29000 | 0.0743          | 4.1222  |
| 0.0017        | 6.9606 | 30000 | 0.0743          | 4.0668  |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1