---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-test-finetuned
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: en-AU
      split: train
      args: en-AU
    metrics:
    - name: Wer
      type: wer
      value: 14.926022628372499
---

<!-- 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-test-finetuned

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: 0.5522
- Wer Ortho: 15.9236
- Wer: 14.9260

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.0009        | 15.15  | 500  | 0.4051          | 14.5587   | 13.5335 |
| 0.0003        | 30.3   | 1000 | 0.4404          | 14.8772   | 13.7511 |
| 0.0002        | 45.45  | 1500 | 0.4655          | 15.5596   | 14.4909 |
| 0.0001        | 60.61  | 2000 | 0.4870          | 15.4231   | 14.3168 |
| 0.0001        | 75.76  | 2500 | 0.5048          | 15.6961   | 14.6649 |
| 0.0           | 90.91  | 3000 | 0.5217          | 15.7871   | 14.7084 |
| 0.0           | 106.06 | 3500 | 0.5368          | 15.9691   | 14.9260 |
| 0.0           | 121.21 | 4000 | 0.5522          | 15.9236   | 14.9260 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2