---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-polyai-enUS_lower_lr
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PolyAI/minds14
      type: PolyAI/minds14
    metrics:
    - name: Wer
      type: wer
      value: 0.38488783943329397
---

<!-- 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-polyai-enUS_lower_lr

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: 0.7730
- Wer Ortho: 0.4022
- Wer: 0.3849

## 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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 2.9571        | 3.33  | 50   | 1.9622          | 0.5077    | 0.4050 |
| 0.5131        | 6.67  | 100  | 0.6540          | 0.4152    | 0.3684 |
| 0.2572        | 10.0  | 150  | 0.6091          | 0.3874    | 0.3524 |
| 0.0974        | 13.33 | 200  | 0.6316          | 0.3745    | 0.3442 |
| 0.0405        | 16.67 | 250  | 0.6686          | 0.3917    | 0.3577 |
| 0.0116        | 20.0  | 300  | 0.7097          | 0.4028    | 0.3766 |
| 0.0049        | 23.33 | 350  | 0.7341          | 0.3954    | 0.3743 |
| 0.0032        | 26.67 | 400  | 0.7510          | 0.4065    | 0.3884 |
| 0.0023        | 30.0  | 450  | 0.7607          | 0.3967    | 0.3778 |
| 0.0018        | 33.33 | 500  | 0.7730          | 0.4022    | 0.3849 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0