---
language:
- id
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_12_0
metrics:
- wer
model-index:
- name: Whisper small ID - Augmented
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_12_0
      type: mozilla-foundation/common_voice_12_0
      config: id
      split: test
      args: id
    metrics:
    - name: Wer
      type: wer
      value: 5.697759963469393
---

<!-- 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 - Augmented

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_12_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1483
- Wer: 5.6978

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3979        | 0.77  | 200  | 0.2141          | 9.7635 |
| 0.2625        | 1.54  | 400  | 0.1705          | 7.3636 |
| 0.1398        | 2.31  | 600  | 0.1551          | 6.9636 |
| 0.0666        | 3.07  | 800  | 0.1678          | 6.2043 |
| 0.0411        | 3.84  | 1000 | 0.1483          | 5.6978 |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2