---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en
  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: 32.99881936245573
---

<!-- 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-en

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: 0.8597
- Wer Ortho: 32.7576
- Wer: 32.9988

## 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     |
|:-------------:|:--------:|:----:|:---------------:|:---------:|:-------:|
| 0.0007        | 17.2414  | 500  | 0.6479          | 32.3874   | 32.3495 |
| 0.0002        | 34.4828  | 1000 | 0.7071          | 32.8809   | 32.9988 |
| 0.0001        | 51.7241  | 1500 | 0.7428          | 32.7576   | 32.9988 |
| 0.0001        | 68.9655  | 2000 | 0.7709          | 32.6959   | 32.9398 |
| 0.0           | 86.2069  | 2500 | 0.7948          | 32.7576   | 33.0579 |
| 0.0           | 103.4483 | 3000 | 0.8179          | 33.0043   | 33.2349 |
| 0.0           | 120.6897 | 3500 | 0.8392          | 32.9426   | 33.1759 |
| 0.0           | 137.9310 | 4000 | 0.8597          | 32.7576   | 32.9988 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1