---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: en-US
      split: train[450:]
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.22434915773353753
---

<!-- 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

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: 0.5913
- Wer Ortho: 0.2340
- Wer: 0.2243

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.7357        | 2.0   | 50   | 0.7179          | 0.2947    | 0.2412 |
| 0.2772        | 4.0   | 100  | 0.4758          | 0.2404    | 0.2113 |
| 0.081         | 6.0   | 150  | 0.5069          | 0.2628    | 0.2282 |
| 0.02          | 8.0   | 200  | 0.5289          | 0.2564    | 0.2297 |
| 0.0044        | 10.0  | 250  | 0.5366          | 0.2452    | 0.2251 |
| 0.0018        | 12.0  | 300  | 0.5565          | 0.2404    | 0.2251 |
| 0.0011        | 14.0  | 350  | 0.5668          | 0.2388    | 0.2259 |
| 0.0009        | 16.0  | 400  | 0.5762          | 0.2364    | 0.2251 |
| 0.0007        | 18.0  | 450  | 0.5847          | 0.2348    | 0.2243 |
| 0.0006        | 20.0  | 500  | 0.5913          | 0.2340    | 0.2243 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3