---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14
  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: 0.33412042502951594
---

<!-- 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-minds14

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: 0.4866
- Wer Ortho: 0.3356
- Wer: 0.3341

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 3.8369        | 0.36  | 5    | 2.6069          | 0.5200    | 0.4044 |
| 1.9739        | 0.71  | 10   | 1.0073          | 0.4411    | 0.4026 |
| 0.728         | 1.07  | 15   | 0.6096          | 0.3948    | 0.3902 |
| 0.3929        | 1.43  | 20   | 0.5288          | 0.4503    | 0.4486 |
| 0.4044        | 1.79  | 25   | 0.4995          | 0.3430    | 0.3430 |
| 0.311         | 2.14  | 30   | 0.4772          | 0.3701    | 0.3701 |
| 0.2404        | 2.5   | 35   | 0.4738          | 0.3134    | 0.3135 |
| 0.1688        | 2.86  | 40   | 0.4700          | 0.3257    | 0.3253 |
| 0.1278        | 3.21  | 45   | 0.4748          | 0.3183    | 0.3164 |
| 0.0775        | 3.57  | 50   | 0.4866          | 0.3356    | 0.3341 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0