---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: whisper-tiny-fo
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ravnursson_asr
      type: ravnursson_asr
      config: ravnursson_asr
      split: None
      args: ravnursson_asr
    metrics:
    - name: Wer
      type: wer
      value: 97.39999999999999
---

<!-- 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. -->

# whisper-tiny-fo

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the ravnursson_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3908
- Wer: 97.4000

## 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: 5
- training_steps: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.43  | 10   | 3.7140          | 118.4000 |
| No log        | 2.86  | 20   | 2.6041          | 100.2    |
| 2.8026        | 4.29  | 30   | 2.4362          | 97.6     |
| 2.8026        | 5.71  | 40   | 2.3908          | 97.4000  |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1