---
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: PolyAI/minds14
      type: PolyAI/minds14
      config: en-US
      split: train
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.40436835891381345
---

<!-- 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 PolyAI/minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5951
- Wer Ortho: 0.4781
- Wer: 0.4044

## 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-06
- 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: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 2.605         | 1.79  | 50   | 2.3450          | 0.5355    | 0.3967 |
| 1.67          | 3.57  | 100  | 1.4800          | 0.5355    | 0.4126 |
| 0.8205        | 5.36  | 150  | 0.8745          | 0.5836    | 0.4787 |
| 0.5984        | 7.14  | 200  | 0.7396          | 0.4923    | 0.4079 |
| 0.4993        | 8.93  | 250  | 0.6831          | 0.4769    | 0.3996 |
| 0.4134        | 10.71 | 300  | 0.6510          | 0.4830    | 0.4032 |
| 0.384         | 12.5  | 350  | 0.6307          | 0.4738    | 0.3961 |
| 0.3286        | 14.29 | 400  | 0.6162          | 0.4806    | 0.4050 |
| 0.3188        | 16.07 | 450  | 0.6062          | 0.4800    | 0.4050 |
| 0.2751        | 17.86 | 500  | 0.6010          | 0.4843    | 0.4097 |
| 0.2568        | 19.64 | 550  | 0.5970          | 0.4750    | 0.4026 |
| 0.237         | 21.43 | 600  | 0.5951          | 0.4781    | 0.4044 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0