---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- srirama/dental
metrics:
- wer
model-index:
- name: Whisper Small - D Notes
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Sample Dental
      type: srirama/dental
      config: default
      split: None
      args: 'config: default, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 6.684121361466194
---

<!-- 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 - D Notes

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sample Dental dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Wer: 6.6841

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0024        | 10.9890 | 1000 | 0.0010          | 7.0692 |
| 0.0002        | 21.9780 | 2000 | 0.0003          | 6.6687 |
| 0.0001        | 32.9670 | 3000 | 0.0001          | 6.6071 |
| 0.0001        | 43.9560 | 4000 | 0.0001          | 6.6841 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1