---
language:
- hi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Swedish
  results: 
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      split: None
      args: 'config: sv-SE, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 51.31886746793579
---

<!-- 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 Small Hi - Swedish

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0765
- Wer: 51.3189

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.5005        | 1.29  | 1000 | 1.7517          | 84.8861 |
| 0.8752        | 2.59  | 2000 | 1.2958          | 68.8688 |
| 0.4382        | 3.88  | 3000 | 1.1835          | 60.4152 |
| 0.0694        | 5.17  | 4000 | 1.1659          | 55.8442 |
| 0.0091        | 6.47  | 5000 | 1.0765          | 51.3189 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.9.0+cu102
- Datasets 2.7.1
- Tokenizers 0.13.2