---
language:
- sv
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-small-sv-extra-data
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0
      type: mozilla-foundation/common_voice_13_0
      config: default
      split: test
      args: 'config: sv, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 22.158468913970783
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
    metrics:
    - name: Wer
      type: wer
      value: 22.158468913970783
---

<!-- 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-sv-extra-data

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_13_0 and the google/fleurs datasets.
It achieves the following results on the evaluation set:
- Loss: 0.3843
- Wer: 22.1585

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3189        | 0.53  | 500  | 0.3610          | 25.2029 |
| 0.1451        | 1.05  | 1000 | 0.3337          | 23.6495 |
| 0.1432        | 1.58  | 1500 | 0.3263          | 22.8908 |
| 0.0572        | 2.1   | 2000 | 0.3284          | 22.1622 |
| 0.0502        | 2.63  | 2500 | 0.3405          | 22.2000 |
| 0.0259        | 3.15  | 3000 | 0.3596          | 22.1924 |
| 0.0246        | 3.68  | 3500 | 0.3650          | 22.2208 |
| 0.0137        | 4.2   | 4000 | 0.3843          | 22.1585 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0