---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: PolyAI/minds14
  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: 0.35780382479950645
---

<!-- 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. -->

# minds14-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: 0.6602
- Wer Ortho: 0.3412
- Wer: 0.3578

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 4.8952        | 1.0   | 28   | 2.9786          | 0.4097    | 0.5373 |
| 2.0364        | 2.0   | 56   | 0.7791          | 0.3813    | 0.4275 |
| 0.5903        | 3.0   | 84   | 0.5917          | 0.3506    | 0.3917 |
| 0.3271        | 4.0   | 112  | 0.5681          | 0.3129    | 0.3381 |
| 0.2543        | 5.0   | 140  | 0.5713          | 0.3365    | 0.3652 |
| 0.1391        | 6.0   | 168  | 0.5896          | 0.3329    | 0.3621 |
| 0.0846        | 7.0   | 196  | 0.6083          | 0.3388    | 0.3658 |
| 0.0481        | 8.0   | 224  | 0.6209          | 0.3583    | 0.3738 |
| 0.0148        | 9.0   | 252  | 0.6625          | 0.3477    | 0.3689 |
| 0.0087        | 10.0  | 280  | 0.6602          | 0.3412    | 0.3578 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3