---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-minds14-en-v2
  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: 0.3695395513577332
---

<!-- 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-finetuned-minds14-en-v2

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: 0.7064
- Wer Ortho: 0.3720
- Wer: 0.3695

## 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: 64
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 1.5939        | 7.14  | 50   | 0.6729          | 0.4294    | 0.4032 |
| 0.1094        | 14.29 | 100  | 0.5254          | 0.3763    | 0.3642 |
| 0.0057        | 21.43 | 150  | 0.5993          | 0.3646    | 0.3607 |
| 0.002         | 28.57 | 200  | 0.6255          | 0.3609    | 0.3601 |
| 0.0013        | 35.71 | 250  | 0.6444          | 0.3652    | 0.3625 |
| 0.0009        | 42.86 | 300  | 0.6603          | 0.3689    | 0.3660 |
| 0.0007        | 50.0  | 350  | 0.6736          | 0.3701    | 0.3678 |
| 0.0006        | 57.14 | 400  | 0.6857          | 0.3726    | 0.3707 |
| 0.0005        | 64.29 | 450  | 0.6965          | 0.3708    | 0.3689 |
| 0.0004        | 71.43 | 500  | 0.7064          | 0.3720    | 0.3695 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3