---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-minds14-en_US-test-finetuned
  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: 0.26380766731643923
---

<!-- 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-en_US-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: 1.0871
- Wer Ortho: 26.8342
- Wer: 0.2638

## 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    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 0.0021        | 17.86  | 500  | 0.7863          | 26.6304   | 0.2534 |
| 0.0002        | 35.71  | 1000 | 0.8689          | 26.7663   | 0.2612 |
| 0.0001        | 53.57  | 1500 | 0.9230          | 27.2418   | 0.2664 |
| 0.0001        | 71.43  | 2000 | 0.9637          | 27.1739   | 0.2664 |
| 0.0           | 89.29  | 2500 | 0.9977          | 26.9022   | 0.2638 |
| 0.0           | 107.14 | 3000 | 1.0277          | 27.1739   | 0.2664 |
| 0.0           | 125.0  | 3500 | 1.0571          | 27.1739   | 0.2671 |
| 0.0           | 142.86 | 4000 | 1.0871          | 26.8342   | 0.2638 |


### Framework versions

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