---
language:
- sa
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- addy88/sanskrit-asr-84
metrics:
- wer
model-index:
- name: Whisper Small Sanskasr - bvkb
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: addy88/sanskrit-asr-84
      type: addy88/sanskrit-asr-84
      config: null
      split: None
      args: 'split: test'
    metrics:
    - name: Wer
      type: wer
      value: 87.73735987188287
---

<!-- 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 Sanskasr - bvkb

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the addy88/sanskrit-asr-84 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7583
- Wer: 87.7374

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.516         | 0.02  | 10   | 1.1614          | 96.7284 |
| 1.0285        | 0.04  | 20   | 0.9667          | 99.4967 |
| 0.9284        | 0.06  | 30   | 0.8885          | 93.6399 |
| 0.8789        | 0.08  | 40   | 0.8437          | 90.8259 |
| 0.8579        | 0.1   | 50   | 0.8159          | 89.4532 |
| 0.8001        | 0.12  | 60   | 0.7957          | 89.4990 |
| 0.8113        | 0.14  | 70   | 0.7807          | 89.1558 |
| 0.7542        | 0.16  | 80   | 0.7698          | 87.9890 |
| 0.7672        | 0.18  | 90   | 0.7610          | 87.7374 |
| 0.7576        | 0.2   | 100  | 0.7583          | 87.7374 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.13.0
- Tokenizers 0.13.3