---
language:
- en
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: minds14
      type: PolyAI/minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 32.88075560802833
---

<!-- 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 minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6734
- Wer Ortho: 32.6959
- Wer: 32.8808

## 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: 5e-05
- train_batch_size: 8
- 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: 8
- training_steps: 225
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 2.8035        | 0.25  | 14   | 0.7206          | 42.1345   | 40.4368 |
| 0.5469        | 0.5   | 28   | 0.5327          | 36.0888   | 36.3046 |
| 0.4968        | 0.75  | 42   | 0.5195          | 34.7933   | 34.7107 |
| 0.5012        | 1.0   | 56   | 0.5551          | 33.5595   | 33.7072 |
| 0.1879        | 1.25  | 70   | 0.5353          | 31.5854   | 31.4640 |
| 0.239         | 1.5   | 84   | 0.5303          | 37.4460   | 40.6139 |
| 0.2082        | 1.75  | 98   | 0.5565          | 31.0302   | 31.2279 |
| 0.2244        | 2.0   | 112  | 0.5540          | 28.5626   | 28.6305 |
| 0.0679        | 2.25  | 126  | 0.5759          | 28.5009   | 28.6305 |
| 0.0637        | 2.5   | 140  | 0.6192          | 50.7094   | 54.0732 |
| 0.072         | 2.75  | 154  | 0.6093          | 31.2770   | 30.9327 |
| 0.0506        | 3.0   | 168  | 0.6302          | 35.2869   | 35.5372 |
| 0.029         | 3.25  | 182  | 0.6299          | 33.4978   | 33.5891 |
| 0.0405        | 3.5   | 196  | 0.6159          | 30.1049   | 30.4014 |
| 0.022         | 3.75  | 210  | 0.6441          | 30.7218   | 30.9917 |
| 0.0332        | 4.0   | 224  | 0.6734          | 32.6959   | 32.8808 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1