transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer vi base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
language:
- vi
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small Mnong
  results: []
---

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

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the MnongAudio dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5531
- Wer: 87.8261

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0666        | 8.93  | 1000 | 2.4189          | 92.3188 |
| 0.0007        | 17.86 | 2000 | 2.4749          | 88.9855 |
| 0.0003        | 26.79 | 3000 | 2.5286          | 87.1014 |
| 0.0002        | 35.71 | 4000 | 2.5531          | 87.8261 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
