---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-PolyAI-minds14
  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: 0.36068476977567887
---

<!-- 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-minds14

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: 0.5565
- Wer Ortho: 0.5120
- Wer: 0.3607

## 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-07
- train_batch_size: 64
- eval_batch_size: 64
- 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    |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|
| 2.3523        | 71.43  | 500  | 2.3552          | 0.6089    | 0.4067 |
| 1.1267        | 142.86 | 1000 | 1.2038          | 0.5922    | 0.4132 |
| 0.5363        | 214.29 | 1500 | 0.7055          | 0.5694    | 0.4014 |
| 0.3846        | 285.71 | 2000 | 0.6171          | 0.5490    | 0.4008 |
| 0.304         | 357.14 | 2500 | 0.5816          | 0.5379    | 0.3890 |
| 0.2428        | 428.57 | 3000 | 0.5644          | 0.5182    | 0.3713 |
| 0.1922        | 500.0  | 3500 | 0.5570          | 0.5139    | 0.3666 |
| 0.1499        | 571.43 | 4000 | 0.5565          | 0.5120    | 0.3607 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1