---
license: apache-2.0
base_model: NbAiLab/nb-whisper-tiny
tags:
- generated_from_trainer
datasets:
- samromur_asr
metrics:
- wer
model-index:
- name: whisper-tiny-no-is-5k-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: 51.60346372051359
---

<!-- 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/blydklsj)
# whisper-tiny-no-is-5k-steps

This model is a fine-tuned version of [NbAiLab/nb-whisper-tiny](https://huggingface.co/NbAiLab/nb-whisper-tiny) on the samromur_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7830
- Wer: 51.6035

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.2696        | 0.1778 | 1000 | 1.3551          | 69.4512 |
| 0.9101        | 0.3556 | 2000 | 0.9833          | 60.0096 |
| 0.7626        | 0.5333 | 3000 | 0.8596          | 54.7590 |
| 0.7316        | 0.7111 | 4000 | 0.8014          | 52.3165 |
| 0.7269        | 0.8889 | 5000 | 0.7830          | 51.6035 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1