---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-en-US
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
      config: en-US
      split: train[450:]
      args: en-US
    metrics:
    - name: Wer
      type: wer
      value: 0.35360094451003543
---

<!-- 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-US

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: 0.6166
- Wer Ortho: 0.3504
- Wer: 0.3536

## 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: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|
| 0.7658        | 1.7857  | 50   | 0.5871          | 0.3948    | 0.3932 |
| 0.2602        | 3.5714  | 100  | 0.4866          | 0.3504    | 0.3501 |
| 0.0796        | 5.3571  | 150  | 0.5121          | 0.3424    | 0.3453 |
| 0.0316        | 7.1429  | 200  | 0.5443          | 0.3374    | 0.3418 |
| 0.0116        | 8.9286  | 250  | 0.5672          | 0.3202    | 0.3253 |
| 0.0034        | 10.7143 | 300  | 0.5966          | 0.3529    | 0.3566 |
| 0.0026        | 12.5    | 350  | 0.6046          | 0.3541    | 0.3583 |
| 0.002         | 14.2857 | 400  | 0.6098          | 0.3498    | 0.3536 |
| 0.002         | 16.0714 | 450  | 0.6146          | 0.3510    | 0.3542 |
| 0.002         | 17.8571 | 500  | 0.6166          | 0.3504    | 0.3536 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1