---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-tiny
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_pfs
      type: rishabhjain16/infer_pfs
      config: en
      split: test
    metrics:
    - type: wer
      value: 42.3
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_myst
      type: rishabhjain16/infer_myst
      config: en
      split: test
    metrics:
    - type: wer
      value: 21.53
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/cmu_wav
      type: rishabhjain16/cmu_wav
      config: en
      split: test
    metrics:
    - type: wer
      value: 27.6
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/infer_cmu
      type: rishabhjain16/infer_cmu
      config: en
      split: test
    metrics:
    - type: wer
      value: 27.61
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: rishabhjain16/libritts_dev_clean
      type: rishabhjain16/libritts_dev_clean
      config: en
      split: test
    metrics:
    - type: wer
      value: 17.92
      name: WER
---

<!-- 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. -->

# openai/whisper-tiny

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the MyST(55 hours) dataset.
It achieves the following results on the evaluation set (MyST 10 hours):
- Loss: 0.5675
- Wer: 20.2661

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3752        | 4.02  | 1000 | 0.4264          | 20.9318 |
| 0.2349        | 8.04  | 2000 | 0.4460          | 19.5872 |
| 0.095         | 13.01 | 3000 | 0.5086          | 20.6995 |
| 0.0416        | 17.02 | 4000 | 0.5504          | 20.7856 |
| 0.0339        | 21.04 | 5000 | 0.5675          | 20.2661 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2