---
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 tiny ID - Augmented
  results:
  - task:
      type: automatic-speech-recognition
      name: 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:
    - type: wer
      value: 14.42705294401177
      name: Wer
    - type: wer
      value: 14.42705294401177
      name: WER
---

<!-- 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 ID - Augmented

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_12_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2874
- Wer: 14.4271

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.6729        | 0.77  | 200  | 0.4170          | 21.8473 |
| 0.5012        | 1.54  | 400  | 0.3465          | 18.2560 |
| 0.3832        | 2.31  | 600  | 0.3097          | 16.0971 |
| 0.2853        | 3.07  | 800  | 0.2970          | 14.3180 |
| 0.2416        | 3.84  | 1000 | 0.2874          | 14.4271 |


### Framework versions

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