---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-tiny-common_voice_17_0-id
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0 id
      type: mozilla-foundation/common_voice_17_0
      config: id
      split: None
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 0.1807044410413476
---

<!-- 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-tiny-common_voice_17_0-id

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_17_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2000
- Wer: 0.1807

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.4911        | 0.4229 | 1000  | 0.4546          | 0.3321 |
| 0.4078        | 0.8458 | 2000  | 0.3520          | 0.2807 |
| 0.2679        | 1.2688 | 3000  | 0.3050          | 0.2421 |
| 0.2423        | 1.6917 | 4000  | 0.2725          | 0.2217 |
| 0.169         | 2.1146 | 5000  | 0.2515          | 0.2184 |
| 0.1646        | 2.5375 | 6000  | 0.2377          | 0.2082 |
| 0.1731        | 2.9605 | 7000  | 0.2189          | 0.1911 |
| 0.1017        | 3.3834 | 8000  | 0.2135          | 0.1970 |
| 0.0985        | 3.8063 | 9000  | 0.2077          | 0.1819 |
| 0.0828        | 4.2292 | 10000 | 0.2070          | 0.1792 |
| 0.06          | 4.6521 | 11000 | 0.1991          | 0.1826 |
| 0.0629        | 5.0751 | 12000 | 0.2012          | 0.1918 |
| 0.0545        | 5.4980 | 13000 | 0.2017          | 0.1864 |
| 0.0392        | 5.9209 | 14000 | 0.1985          | 0.1910 |
| 0.0338        | 6.3438 | 15000 | 0.1989          | 0.1807 |
| 0.0312        | 6.7668 | 16000 | 0.1982          | 0.1945 |
| 0.0237        | 7.1897 | 17000 | 0.1998          | 0.1842 |
| 0.0223        | 7.6126 | 18000 | 0.1994          | 0.1800 |
| 0.0192        | 8.0355 | 19000 | 0.1993          | 0.1806 |
| 0.0158        | 8.4584 | 20000 | 0.2000          | 0.1807 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.1.0
- Datasets 2.19.1
- Tokenizers 0.19.1