---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- PolyAI/minds14
metrics:
- wer
model-index:
- name: whisper-tiny-ashok
  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: 0.35301353013530135
---

<!-- 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-ashok

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: 0.8440
- Wer Ortho: 34.6847
- Wer: 0.3530

## 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: 5e-05
- train_batch_size: 32
- 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: 50
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.0234        | 6.67  | 100  | 0.6639          | 34.2986   | 0.3383 |
| 0.003         | 13.33 | 200  | 0.7587          | 33.9768   | 0.3401 |
| 0.0005        | 20.0  | 300  | 0.7870          | 34.2342   | 0.3475 |
| 0.0003        | 26.67 | 400  | 0.8045          | 35.1351   | 0.3567 |
| 0.0002        | 33.33 | 500  | 0.8144          | 35.5856   | 0.3610 |
| 0.0001        | 40.0  | 600  | 0.8262          | 35.5212   | 0.3604 |
| 0.0001        | 46.67 | 700  | 0.8341          | 35.3282   | 0.3592 |
| 0.0001        | 53.33 | 800  | 0.8397          | 35.1995   | 0.3579 |
| 0.0001        | 60.0  | 900  | 0.8426          | 34.7490   | 0.3536 |
| 0.0001        | 66.67 | 1000 | 0.8440          | 34.6847   | 0.3530 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3