---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-us-ZA
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.27835051546391754
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/soundofai/huggingface-audio-course-unit5-handson-af/runs/ym0ygfa9)
# whisper-tiny-us-ZA

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6915
- Wer Ortho: 0.2821
- Wer: 0.2784

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 5
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.3413        | 3.125  | 100  | 0.4281          | 0.2727    | 0.2474 |
| 0.0659        | 6.25   | 200  | 0.4672          | 0.2754    | 0.2526 |
| 0.0076        | 9.375  | 300  | 0.5252          | 0.3035    | 0.2899 |
| 0.0019        | 12.5   | 400  | 0.5568          | 0.2874    | 0.2758 |
| 0.0009        | 15.625 | 500  | 0.5804          | 0.2901    | 0.2771 |
| 0.0006        | 18.75  | 600  | 0.5947          | 0.2861    | 0.2732 |
| 0.0005        | 21.875 | 700  | 0.6062          | 0.2848    | 0.2745 |
| 0.0004        | 25.0   | 800  | 0.6170          | 0.2834    | 0.2745 |
| 0.0003        | 28.125 | 900  | 0.6261          | 0.2834    | 0.2745 |
| 0.0003        | 31.25  | 1000 | 0.6346          | 0.2781    | 0.2719 |
| 0.0002        | 34.375 | 1100 | 0.6423          | 0.2794    | 0.2732 |
| 0.0002        | 37.5   | 1200 | 0.6497          | 0.2794    | 0.2732 |
| 0.0002        | 40.625 | 1300 | 0.6563          | 0.2794    | 0.2732 |
| 0.0002        | 43.75  | 1400 | 0.6627          | 0.2794    | 0.2732 |
| 0.0001        | 46.875 | 1500 | 0.6680          | 0.2941    | 0.2874 |
| 0.0001        | 50.0   | 1600 | 0.6736          | 0.2874    | 0.2809 |
| 0.0001        | 53.125 | 1700 | 0.6781          | 0.2874    | 0.2809 |
| 0.0001        | 56.25  | 1800 | 0.6833          | 0.2874    | 0.2809 |
| 0.0001        | 59.375 | 1900 | 0.6876          | 0.2834    | 0.2796 |
| 0.0001        | 62.5   | 2000 | 0.6915          | 0.2821    | 0.2784 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1