---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: openai/whisper-tiny
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: sv_se
      split: validation
      args: sv_se
    metrics:
    - name: Wer
      type: wer
      value: 168.6092926712438
---

<!-- 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. -->

# openai/whisper-tiny

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0456
- Wer: 168.6093

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- training_steps: 112
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5299        | 0.1   | 11   | 1.5622          | 219.6711 |
| 1.1908        | 0.2   | 22   | 1.3652          | 192.2401 |
| 1.1161        | 0.29  | 33   | 1.1921          | 200.2395 |
| 0.9216        | 1.05  | 44   | 1.1263          | 186.5240 |
| 0.8441        | 1.15  | 55   | 1.0946          | 179.3230 |
| 0.8505        | 1.25  | 66   | 1.0748          | 159.6839 |
| 0.7844        | 2.01  | 77   | 1.0585          | 163.2924 |
| 0.7208        | 2.11  | 88   | 1.0491          | 158.1031 |
| 0.6481        | 2.21  | 99   | 1.0468          | 158.5183 |
| 0.7912        | 2.3   | 110  | 1.0456          | 168.6093 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2