---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-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: 0.2833530106257379
---

<!-- 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

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: 0.7473
- Wer Ortho: 0.2788
- Wer: 0.2834

## 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: 3.220378398329722e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9850038588304092,0.9902432649395926) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 205
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| No log        | 1.0   | 28   | 2.9124          | 0.5305    | 0.3991 |
| No log        | 2.0   | 56   | 1.3721          | 0.4516    | 0.4091 |
| No log        | 3.0   | 84   | 0.6397          | 0.3856    | 0.3872 |
| No log        | 4.0   | 112  | 0.5424          | 0.3849    | 0.3819 |
| No log        | 5.0   | 140  | 0.5124          | 0.4460    | 0.4410 |
| No log        | 6.0   | 168  | 0.5153          | 0.3479    | 0.3477 |
| No log        | 7.0   | 196  | 0.5565          | 0.3418    | 0.3424 |
| No log        | 8.0   | 224  | 0.5882          | 0.3208    | 0.3229 |
| No log        | 9.0   | 252  | 0.6248          | 0.3356    | 0.3371 |
| No log        | 10.0  | 280  | 0.6545          | 0.3282    | 0.3300 |
| No log        | 11.0  | 308  | 0.7122          | 0.3060    | 0.3093 |
| No log        | 12.0  | 336  | 0.7473          | 0.2788    | 0.2834 |
| No log        | 13.0  | 364  | 0.7717          | 0.3072    | 0.3093 |
| No log        | 14.0  | 392  | 0.7852          | 0.3424    | 0.3447 |
| No log        | 15.0  | 420  | 0.8127          | 0.3307    | 0.3318 |
| No log        | 16.0  | 448  | 0.8471          | 0.3300    | 0.3294 |
| No log        | 17.0  | 476  | 0.8614          | 0.3405    | 0.3406 |
| 0.4338        | 18.0  | 504  | 0.8992          | 0.3627    | 0.3630 |
| 0.4338        | 19.0  | 532  | 0.9157          | 0.3640    | 0.3648 |
| 0.4338        | 20.0  | 560  | 0.9274          | 0.3578    | 0.3589 |
| 0.4338        | 21.0  | 588  | 0.9275          | 0.3387    | 0.3377 |
| 0.4338        | 22.0  | 616  | 0.9371          | 0.3381    | 0.3371 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1
- Datasets 2.13.2.dev1
- Tokenizers 0.13.3