---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-base-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: 0.1183813634043343
---

<!-- 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-base-common_voice_17_0-id

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_17_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1441
- Wer: 0.1184

## 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    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.3523        | 0.4229 | 1000  | 0.3129          | 0.2365 |
| 0.3002        | 0.8458 | 2000  | 0.2391          | 0.1964 |
| 0.1718        | 1.2688 | 3000  | 0.2049          | 0.1659 |
| 0.1537        | 1.6917 | 4000  | 0.1817          | 0.1516 |
| 0.0807        | 2.1146 | 5000  | 0.1643          | 0.1499 |
| 0.089         | 2.5375 | 6000  | 0.1562          | 0.1348 |
| 0.0883        | 2.9605 | 7000  | 0.1452          | 0.1268 |
| 0.0368        | 3.3834 | 8000  | 0.1446          | 0.1324 |
| 0.0463        | 3.8063 | 9000  | 0.1401          | 0.1286 |
| 0.0278        | 4.2292 | 10000 | 0.1436          | 0.1181 |
| 0.0157        | 4.6521 | 11000 | 0.1406          | 0.1125 |
| 0.0201        | 5.0751 | 12000 | 0.1392          | 0.1144 |
| 0.0121        | 5.4980 | 13000 | 0.1405          | 0.1129 |
| 0.0074        | 5.9209 | 14000 | 0.1385          | 0.1195 |
| 0.0064        | 6.3438 | 15000 | 0.1410          | 0.1115 |
| 0.0066        | 6.7668 | 16000 | 0.1415          | 0.1184 |
| 0.0029        | 7.1897 | 17000 | 0.1426          | 0.1190 |
| 0.0024        | 7.6126 | 18000 | 0.1429          | 0.1178 |
| 0.0021        | 8.0355 | 19000 | 0.1434          | 0.1180 |
| 0.0018        | 8.4584 | 20000 | 0.1441          | 0.1184 |


### Framework versions

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