transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer dk dataset:mozilla-foundation/common_voice_11_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- dk
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small dk
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: da
      split: test
      args: 'config: dk, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 29.494396801178514
---

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

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: 0.6207
- Wer: 29.4944

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4214        | 1.37  | 200  | 0.5155          | 32.5933 |
| 0.1758        | 2.75  | 400  | 0.4674          | 29.5260 |
| 0.0591        | 4.12  | 600  | 0.5032          | 30.5361 |
| 0.0258        | 5.5   | 800  | 0.5336          | 30.0573 |
| 0.017         | 6.87  | 1000 | 0.5676          | 29.2419 |
| 0.0067        | 8.25  | 1200 | 0.5738          | 29.1209 |
| 0.0046        | 9.62  | 1400 | 0.5981          | 29.2839 |
| 0.0027        | 11.0  | 1600 | 0.6114          | 29.4418 |
| 0.0021        | 12.37 | 1800 | 0.6184          | 29.4155 |
| 0.002         | 13.75 | 2000 | 0.6207          | 29.4944 |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
