README.md

---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- ASR
- Papiamentu
- Whisper
- Speech Recognition
- generated_from_trainer
datasets:
- sonnygeorge/papi_asr_corpus
metrics:
- wer
model-index:
- name: Whisper Tiny Papiamentu
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Papi ASR
      type: sonnygeorge/papi_asr_corpus
    metrics:
    - name: Wer
      type: wer
      value: 43.55778449738181
---

<!-- 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 Papiamentu

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Papi ASR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5097
- Wer: 43.5578
- Cer: 21.6799

## 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: 3
- training_steps: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.5202        | 0.07  | 50   | 0.6086          | 53.0423 | 30.5887 |
| 0.4887        | 0.15  | 100  | 0.5316          | 45.0254 | 21.4973 |
| 0.4872        | 0.22  | 150  | 0.5097          | 43.5578 | 21.6799 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0