---
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-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: 0.28512396694214875
---

<!-- 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: 0.7381
- Wer Ortho: 0.2850
- Wer: 0.2851

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 0
- 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: 500

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|
| 0.9105        | 1.7857  | 50   | 0.6418          | 0.4115    | 0.3937 |
| 0.2535        | 3.5714  | 100  | 0.5773          | 0.3337    | 0.3164 |
| 0.0887        | 5.3571  | 150  | 0.6295          | 0.3368    | 0.3182 |
| 0.0288        | 7.1429  | 200  | 0.6449          | 0.3381    | 0.3211 |
| 0.0198        | 8.9286  | 250  | 0.6932          | 0.4170    | 0.4203 |
| 0.0092        | 10.7143 | 300  | 0.6835          | 0.3152    | 0.3058 |
| 0.0134        | 12.5    | 350  | 0.7404          | 0.3288    | 0.3264 |
| 0.0096        | 14.2857 | 400  | 0.7067          | 0.3374    | 0.3312 |
| 0.0073        | 16.0714 | 450  | 0.7303          | 0.3122    | 0.3081 |
| 0.0056        | 17.8571 | 500  | 0.7381          | 0.2850    | 0.2851 |


### Framework versions

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