---
license: apache-2.0
base_model: NbAiLab/nb-whisper-large
tags:
- generated_from_trainer
datasets:
- samromur_asr
metrics:
- wer
model-index:
- name: whisper-large-no-is-145h-30k-steps
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: samromur_asr
      type: samromur_asr
      config: samromur_asr
      split: test
      args: samromur_asr
    metrics:
    - name: Wer
      type: wer
      value: 8.020304568527918
---

<!-- 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/a8dup09b)
# whisper-large-no-is-145h-30k-steps

This model is a fine-tuned version of [NbAiLab/nb-whisper-large](https://huggingface.co/NbAiLab/nb-whisper-large) on the samromur_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1280
- Wer: 8.0203

## 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     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.3237        | 0.1778 | 1000  | 0.3331          | 24.9280 |
| 0.2334        | 0.3556 | 2000  | 0.2369          | 19.2033 |
| 0.1932        | 0.5333 | 3000  | 0.2121          | 16.7584 |
| 0.1681        | 0.7111 | 4000  | 0.1874          | 14.9669 |
| 0.1487        | 0.8889 | 5000  | 0.1720          | 13.8274 |
| 0.0911        | 1.0667 | 6000  | 0.1644          | 13.2541 |
| 0.0765        | 1.2444 | 7000  | 0.1577          | 12.3332 |
| 0.0843        | 1.4222 | 8000  | 0.1469          | 11.8722 |
| 0.0797        | 1.6    | 9000  | 0.1437          | 11.3156 |
| 0.0778        | 1.7778 | 10000 | 0.1365          | 10.9298 |
| 0.0789        | 1.9556 | 11000 | 0.1329          | 10.7554 |
| 0.039         | 2.1333 | 12000 | 0.1353          | 10.3625 |
| 0.0394        | 2.3111 | 13000 | 0.1399          | 10.2872 |
| 0.0438        | 2.4889 | 14000 | 0.1357          | 10.0926 |
| 0.0365        | 2.6667 | 15000 | 0.1287          | 9.8632  |
| 0.0406        | 2.8444 | 16000 | 0.1266          | 9.6435  |
| 0.0193        | 3.0222 | 17000 | 0.1284          | 9.3258  |
| 0.0181        | 3.2    | 18000 | 0.1309          | 9.3019  |
| 0.0215        | 3.3778 | 19000 | 0.1317          | 9.1299  |
| 0.0207        | 3.5556 | 20000 | 0.1287          | 8.8767  |
| 0.0185        | 3.7333 | 21000 | 0.1285          | 8.8731  |
| 0.0162        | 3.9111 | 22000 | 0.1272          | 8.6581  |
| 0.007         | 4.0889 | 23000 | 0.1285          | 8.6175  |
| 0.0076        | 4.2667 | 24000 | 0.1296          | 8.3655  |
| 0.0074        | 4.4444 | 25000 | 0.1277          | 8.4037  |
| 0.0076        | 4.6222 | 26000 | 0.1289          | 8.3464  |
| 0.006         | 4.8    | 27000 | 0.1257          | 8.1756  |
| 0.0067        | 4.9778 | 28000 | 0.1252          | 8.0979  |
| 0.0025        | 5.1556 | 29000 | 0.1269          | 8.0322  |
| 0.0032        | 5.3333 | 30000 | 0.1280          | 8.0203  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1