---
language:
- ka
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Tiny Ka
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice
      type: mozilla-foundation/common_voice_16_1
      config: ka
      split: test
      args: ka
    metrics:
    - name: Wer
      type: wer
      value: 134.83959527973963
---

<!-- 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 Ka

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0988
- Wer: 134.8396

## 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: 0.003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.0576        | 1.45  | 1000 | 5.1841          | 158.1475 |
| 4.6405        | 2.9   | 2000 | 4.8881          | 131.9237 |
| 4.0627        | 4.35  | 3000 | 4.9336          | 143.5772 |
| 3.781         | 5.8   | 4000 | 4.9113          | 129.0976 |
| 3.0831        | 7.25  | 5000 | 5.0988          | 134.8396 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2