---
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-en
  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: 0.33766233766233766
---

<!-- 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-en

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: 0.8729
- Wer Ortho: 0.3344
- Wer: 0.3377

## 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
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:--------:|:----:|:---------------:|:---------:|:------:|
| 0.0006        | 17.8571  | 500  | 0.6617          | 0.3251    | 0.3264 |
| 0.0002        | 35.7143  | 1000 | 0.7217          | 0.3257    | 0.3270 |
| 0.0001        | 53.5714  | 1500 | 0.7577          | 0.3226    | 0.3247 |
| 0.0001        | 71.4286  | 2000 | 0.7870          | 0.3337    | 0.3347 |
| 0.0           | 89.2857  | 2500 | 0.8109          | 0.3325    | 0.3341 |
| 0.0           | 107.1429 | 3000 | 0.8329          | 0.3356    | 0.3377 |
| 0.0           | 125.0    | 3500 | 0.8529          | 0.3344    | 0.3371 |
| 0.0           | 142.8571 | 4000 | 0.8729          | 0.3344    | 0.3377 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1