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---
language:
- vi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium VI - Multi - Augmented
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: vi
split: test
args: vi
metrics:
- type: wer
value: 16.659355121737224
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: vi
split: test
metrics:
- type: wer
value: 16.63
name: WER
- type: cer
value: 7.74
name: CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: vi_vn
split: test
metrics:
- type: wer
value: 9.04
name: WER
- type: cer
value: 4.81
name: CER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: vivos
type: vivos
split: test
metrics:
- type: wer
value: 8.53
name: WER
- type: cer
value: 3.67
name: CER
---
<!-- 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 Medium VI - Multi - Augmented
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3696
- Wer: 16.6594
- Cer: 7.7625
## 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: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.1992 | 1.8 | 1000 | 0.2726 | 17.4929 | 8.2562 |
| 0.0402 | 3.6 | 2000 | 0.3317 | 17.4929 | 8.2588 |
| 0.0073 | 5.4 | 3000 | 0.3429 | 17.6793 | 8.8913 |
| 0.0014 | 7.19 | 4000 | 0.3599 | 19.0283 | 9.5103 |
| 0.0006 | 8.99 | 5000 | 0.3696 | 16.6594 | 7.7625 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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