---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- Ransaka/SinhalaASR
metrics:
- wer
model-index:
- name: whisper-tiny-sinhala-20k
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: sinhala_asr
      type: sinhala_asr
      config: default
      split: test
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 92.99603723159156
---

<!-- 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-sinhala-20k

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the sinhala_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2433
- Wer: 92.9960

## 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: 8
- eval_batch_size: 16
- 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4207        | 0.4   | 1000 | 0.3978          | 221.9058 |
| 0.2966        | 0.8   | 2000 | 0.3009          | 136.3423 |
| 0.226         | 1.2   | 3000 | 0.2661          | 97.6638  |
| 0.2224        | 1.6   | 4000 | 0.2510          | 92.3279  |
| 0.2034        | 2.0   | 5000 | 0.2433          | 92.9960  |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0