transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:google/fleurs base_model:arun100/whisper-base-vi-1 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: arun100/whisper-base-vi-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Vietnamese
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs vi_vn
      type: google/fleurs
      config: vi_vn
      split: test
      args: vi_vn
    metrics:
    - name: Wer
      type: wer
      value: 31.03382013835511
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Base Vietnamese

This model is a fine-tuned version of [arun100/whisper-base-vi-1](https://huggingface.co/arun100/whisper-base-vi-1) on the google/fleurs vi_vn dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6949
- Wer: 31.0338

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5823        | 43.0  | 500  | 0.7964          | 37.8978 |
| 0.3312        | 86.0  | 1000 | 0.6997          | 33.7125 |
| 0.2009        | 130.0 | 1500 | 0.6784          | 32.7479 |
| 0.1271        | 173.0 | 2000 | 0.6760          | 31.9985 |
| 0.0815        | 217.0 | 2500 | 0.6799          | 31.3028 |
| 0.0561        | 260.0 | 3000 | 0.6851          | 31.2337 |
| 0.0438        | 304.0 | 3500 | 0.6896          | 31.7256 |
| 0.0367        | 347.0 | 4000 | 0.6928          | 31.5949 |
| 0.0331        | 391.0 | 4500 | 0.6949          | 31.0338 |
| 0.0317        | 434.0 | 5000 | 0.6957          | 31.0453 |


### Framework versions

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