transformers pytorch whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer nl dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- nl
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Tiny FT NL_bs32
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0, voxpopuli
      type: mozilla-foundation/common_voice_13_0
      config: nl
      split: test
      args: 'config: nl, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 97.70335601499603
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Tiny FT NL_bs32

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 13.0, voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2896
- Wer: 97.7034

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3004        | 0.1   | 1000  | 0.3763          | 82.0359 |
| 0.1669        | 1.07  | 2000  | 0.3136          | 53.1062 |
| 0.1276        | 2.03  | 3000  | 0.2915          | 64.4126 |
| 0.1146        | 2.13  | 4000  | 0.3259          | 60.0555 |
| 0.0758        | 3.1   | 5000  | 0.3042          | 73.8444 |
| 0.059         | 4.06  | 6000  | 0.3088          | 83.9768 |
| 0.0554        | 5.03  | 7000  | 0.2905          | 81.0178 |
| 0.0503        | 5.13  | 8000  | 0.2877          | 88.2464 |
| 0.0499        | 6.1   | 9000  | 0.3116          | 91.4979 |
| 0.0493        | 7.06  | 10000 | 0.2896          | 97.7034 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.1
- Datasets 2.14.7
- Tokenizers 0.14.1
