---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-small-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: 0.16172444196946495
---

<!-- 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-small-id

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_17_0 id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3506
- Wer: 0.1617

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0547        | 3.8462  | 1000 | 0.2570          | 0.1687 |
| 0.0034        | 7.6923  | 2000 | 0.3144          | 0.1589 |
| 0.0011        | 11.5385 | 3000 | 0.3358          | 0.1615 |
| 0.0007        | 15.3846 | 4000 | 0.3460          | 0.1614 |
| 0.0006        | 19.2308 | 5000 | 0.3506          | 0.1617 |


### Framework versions

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