---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-medium-common_voice_17_0-id-10000
  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: 0.04241496125110214
---

<!-- 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-medium-common_voice_17_0-id-10000

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_17_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0574
- Wer: 0.0424

## 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
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 0.132         | 0.8457 | 1000  | 0.0963          | 0.0747 |
| 0.0503        | 1.6913 | 2000  | 0.0664          | 0.0526 |
| 0.023         | 2.5370 | 3000  | 0.0628          | 0.0727 |
| 0.011         | 3.3827 | 4000  | 0.0593          | 0.0437 |
| 0.0033        | 4.2283 | 5000  | 0.0575          | 0.0407 |
| 0.0017        | 5.0740 | 6000  | 0.0574          | 0.0448 |
| 0.0013        | 5.9197 | 7000  | 0.0554          | 0.0386 |
| 0.002         | 6.7653 | 8000  | 0.0555          | 0.0426 |
| 0.0002        | 7.6110 | 9000  | 0.0571          | 0.0421 |
| 0.0005        | 8.4567 | 10000 | 0.0574          | 0.0424 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1