---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-PolyAI-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: 0.33392963625521765
---

<!-- 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-PolyAI-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: 0.5770
- Wer Ortho: 0.3441
- Wer: 0.3339

## 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_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 2.1657        | 1.0   | 28   | 1.5460          | 0.4913    | 0.4168 |
| 0.4751        | 2.0   | 56   | 0.5582          | 0.3872    | 0.3757 |
| 0.346         | 3.0   | 84   | 0.5050          | 0.3622    | 0.3518 |
| 0.2062        | 4.0   | 112  | 0.4995          | 0.3797    | 0.3661 |
| 0.1223        | 5.0   | 140  | 0.5165          | 0.3547    | 0.3435 |
| 0.069         | 6.0   | 168  | 0.5367          | 0.3516    | 0.3351 |
| 0.0311        | 7.0   | 196  | 0.5545          | 0.3741    | 0.3643 |
| 0.013         | 8.0   | 224  | 0.5766          | 0.3822    | 0.3661 |
| 0.0075        | 9.0   | 252  | 0.5770          | 0.3441    | 0.3339 |
| 0.0037        | 10.0  | 280  | 0.5977          | 0.3485    | 0.3423 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.13.1
- Tokenizers 0.13.3