---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-ft-PolyAI-minds-14-enUS
  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: 0.3689492325855962
---

<!-- 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-ft-PolyAI-minds-14-enUS

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: 0.6365
- Wer Ortho: 0.3763
- Wer: 0.3689

## 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: 4e-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: 100
- training_steps: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 2.9861        | 0.89  | 25   | 1.7468          | 0.5219    | 0.4038 |
| 0.8551        | 1.79  | 50   | 0.5897          | 0.8075    | 0.7928 |
| 0.3477        | 2.68  | 75   | 0.5229          | 0.6206    | 0.6198 |
| 0.151         | 3.57  | 100  | 0.5565          | 0.6971    | 0.6895 |
| 0.0895        | 4.46  | 125  | 0.5740          | 0.4812    | 0.4752 |
| 0.0373        | 5.36  | 150  | 0.5987          | 0.4479    | 0.4416 |
| 0.0232        | 6.25  | 175  | 0.6463          | 0.3751    | 0.3660 |
| 0.015         | 7.14  | 200  | 0.6365          | 0.3763    | 0.3689 |


### Framework versions

- Transformers 4.33.0
- Pytorch 1.12.1+cu116
- Datasets 2.14.4
- Tokenizers 0.12.1