transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:google/fleurs base_model:arun100/whisper-base-id-1 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: arun100/whisper-base-id-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Indonesian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs id_id
      type: google/fleurs
      config: id_id
      split: test
      args: id_id
    metrics:
    - name: Wer
      type: wer
      value: 26.74778761061947
---

<!-- 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 Base Indonesian

This model is a fine-tuned version of [arun100/whisper-base-id-1](https://huggingface.co/arun100/whisper-base-id-1) on the google/fleurs id_id dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5254
- Wer: 26.7478

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3799        | 45.0  | 500  | 0.5510          | 28.5103 |
| 0.1679        | 90.0  | 1000 | 0.5254          | 26.7478 |
| 0.0785        | 136.0 | 1500 | 0.5336          | 27.1386 |
| 0.0408        | 181.0 | 2000 | 0.5439          | 27.1755 |
| 0.0266        | 227.0 | 2500 | 0.5513          | 27.0354 |
| 0.02          | 272.0 | 3000 | 0.5569          | 28.0826 |
| 0.0159        | 318.0 | 3500 | 0.5612          | 28.5767 |
| 0.0136        | 363.0 | 4000 | 0.5645          | 30.1254 |
| 0.0124        | 409.0 | 4500 | 0.5667          | 28.7611 |
| 0.012         | 454.0 | 5000 | 0.5674          | 28.7021 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
