---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-en-us
  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: 0.35400516795865633
---

<!-- 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-en-us

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: 0.7195
- Wer Ortho: 0.3560
- Wer: 0.3540

## 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.8452        | 1.79  | 50   | 0.8160          | 0.3890    | 0.3534 |
| 0.3172        | 3.57  | 100  | 0.5341          | 0.3573    | 0.3547 |
| 0.1191        | 5.36  | 150  | 0.5525          | 0.3284    | 0.3217 |
| 0.0363        | 7.14  | 200  | 0.6061          | 0.3472    | 0.3456 |
| 0.0099        | 8.93  | 250  | 0.6240          | 0.3546    | 0.3540 |
| 0.0036        | 10.71 | 300  | 0.6596          | 0.3560    | 0.3527 |
| 0.0019        | 12.5  | 350  | 0.6777          | 0.3513    | 0.3508 |
| 0.0012        | 14.29 | 400  | 0.6946          | 0.3540    | 0.3527 |
| 0.0009        | 16.07 | 450  | 0.7079          | 0.3526    | 0.3514 |
| 0.0007        | 17.86 | 500  | 0.7195          | 0.3560    | 0.3540 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0