---
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
datasets:
- David-Mazi/whisper-trial
metrics:
- wer
model-index:
- name: Whisper Tiny En Vox - David Mazi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: whisper-trial
      type: David-Mazi/whisper-trial
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 70.06333225073075
---

<!-- 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 En Vox - David Mazi

This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the whisper-trial dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0019
- Wer: 70.0633

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2694        | 4.0   | 100  | 0.1224          | 77.4886 |
| 0.0232        | 8.0   | 200  | 0.0165          | 69.1336 |
| 0.0035        | 12.0  | 300  | 0.0032          | 80.3548 |
| 0.0022        | 16.0  | 400  | 0.0021          | 68.5044 |
| 0.0019        | 20.0  | 500  | 0.0019          | 70.0633 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0