---
language:
- lg
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- tericlabs
metrics:
- wer
model-index:
- name: Whisper Small ganda
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Yogera data
      type: tericlabs
      config: lg
      split: test
      args: lg
    metrics:
    - name: Wer
      type: wer
      value: 54.276315789473685
---

<!-- 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 ganda

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yogera data dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4937
- Wer: 54.2763

## 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: 8
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.9882        | 26.0  | 500  | 1.4647          | 54.9342 |
| 0.0026        | 52.0  | 1000 | 1.3967          | 60.8553 |
| 0.0002        | 78.0  | 1500 | 1.4295          | 57.8947 |
| 0.0001        | 105.0 | 2000 | 1.4494          | 58.2237 |
| 0.0001        | 131.0 | 2500 | 1.4713          | 53.9474 |
| 0.0001        | 157.0 | 3000 | 1.4835          | 54.2763 |
| 0.0001        | 184.0 | 3500 | 1.4908          | 54.2763 |
| 0.0001        | 210.0 | 4000 | 1.4937          | 54.2763 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0