---
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
metrics:
- wer
model-index:
- name: whisper-small-test
  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: 30.900127226463102
---

<!-- 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-test

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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4846
- Wer: 30.9001

## 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: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5133        | 0.64  | 500  | 0.5562          | 38.3826 |
| 0.3764        | 1.28  | 1000 | 0.4754          | 34.1921 |
| 0.3501        | 1.92  | 1500 | 0.4554          | 32.8509 |
| 0.222         | 2.55  | 2000 | 0.4399          | 32.3844 |
| 0.1283        | 3.19  | 2500 | 0.4440          | 32.0081 |
| 0.1575        | 3.83  | 3000 | 0.4295          | 31.8225 |
| 0.1205        | 4.47  | 3500 | 0.4410          | 31.0459 |
| 0.0992        | 5.11  | 4000 | 0.4505          | 31.1042 |
| 0.0941        | 5.75  | 4500 | 0.4551          | 30.8498 |
| 0.0627        | 6.39  | 5000 | 0.4696          | 31.5999 |
| 0.0652        | 7.02  | 5500 | 0.4761          | 31.8013 |
| 0.0573        | 7.66  | 6000 | 0.4846          | 30.9001 |


### Framework versions

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