---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- atulksingh/mypin-voice-dataset
metrics:
- wer
model-index:
- name: Whisper Base myPin
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Domain Based voice
      type: atulksingh/mypin-voice-dataset
      config: default
      split: None
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 3.9215686274509802
---

<!-- 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 Base myPin

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Domain Based voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0078
- Wer: 3.9216

## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0007        | 100.0 | 500  | 0.0086          | 3.9216 |
| 0.0003        | 200.0 | 1000 | 0.0079          | 3.9216 |
| 0.0002        | 300.0 | 1500 | 0.0078          | 3.9216 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1