---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-dv
  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: 0.3520671834625323
---

<!-- 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-dv

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: 0.6490
- Wer Ortho: 0.3567
- Wer: 0.3521

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Wer Ortho |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|
| 0.022         | 1.0   | 28   | 0.5935          | 0.3605 | 0.3661    |
| 0.0158        | 2.0   | 56   | 0.6233          | 0.3463 | 0.3499    |
| 0.0067        | 3.0   | 84   | 0.6469          | 0.3546 | 0.3521    |
| 0.0066        | 3.57  | 100  | 0.6490          | 0.3567 | 0.3521    |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3