---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Refined
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 15.384615384615385
---

<!-- 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 Refined

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8921
- Wer: 15.3846

## 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: 5e-08
- train_batch_size: 16
- eval_batch_size: 8
- 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: 250
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0045        | 400.0  | 400  | 0.9209          | 30.7692 |
| 0.0008        | 800.0  | 800  | 0.8990          | 15.3846 |
| 0.0003        | 1200.0 | 1200 | 0.8957          | 15.3846 |
| 0.0002        | 1600.0 | 1600 | 0.8931          | 15.3846 |
| 0.0001        | 2000.0 | 2000 | 0.8927          | 15.3846 |
| 0.0001        | 2400.0 | 2400 | 0.8927          | 15.3846 |
| 0.0001        | 2800.0 | 2800 | 0.8919          | 15.3846 |
| 0.0001        | 3200.0 | 3200 | 0.8912          | 15.3846 |
| 0.0001        | 3600.0 | 3600 | 0.8918          | 15.3846 |
| 0.0001        | 4000.0 | 4000 | 0.8921          | 15.3846 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1