---
language:
- pa
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Panjabi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: pa-IN
      split: test
      args: pa-IN
    metrics:
    - name: Wer
      type: wer
      value: 36.10043556238791
---

<!-- 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 Small Panjabi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6084
- Wer: 36.1004

## 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: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.349         | 5.86  | 100  | 0.4664          | 49.1929 |
| 0.0175        | 11.74 | 200  | 0.4633          | 39.1494 |
| 0.0052        | 17.63 | 300  | 0.5317          | 37.7146 |
| 0.0014        | 23.51 | 400  | 0.5521          | 36.4079 |
| 0.0009        | 29.4  | 500  | 0.5731          | 35.4599 |
| 0.0002        | 35.29 | 600  | 0.5806          | 35.6649 |
| 0.0001        | 41.17 | 700  | 0.5933          | 35.7161 |
| 0.0001        | 47.06 | 800  | 0.6016          | 35.9211 |
| 0.0001        | 52.91 | 900  | 0.6067          | 36.0492 |
| 0.0001        | 58.8  | 1000 | 0.6084          | 36.1004 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2