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---
language:
- vi
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: openai/whisper-large-v2
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 vi
type: mozilla-foundation/common_voice_11_0
config: vi
split: test
args: vi
metrics:
- type: wer
value: 15.771
name: Wer
- type: cer
value: 7.6691
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. -->
# openai/whisper-large-v2
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4041
- Wer: 15.7710
- Cer: 7.6691
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
Training data:
* [mozilla-foundation/common_voice_11_0](https://huggingface.co/openai/whisper-large-v2)
* [google/fleurs](https://huggingface.co/datasets/google/fleurs)
Evaluation data:
* [mozilla-foundation/common_voice_11_0](https://huggingface.co/openai/whisper-large-v2)
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-07
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 24
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.3983 | 0.1 | 500 | 0.5338 | 19.5876 | 10.6391 |
| 0.2277 | 1.08 | 1000 | 0.4134 | 16.5826 | 8.2668 |
| 0.172 | 2.05 | 1500 | 0.3968 | 16.3084 | 7.9787 |
| 0.1823 | 3.03 | 2000 | 0.3956 | 16.1768 | 7.8159 |
| 0.1445 | 4.0 | 2500 | 0.3955 | 16.0342 | 7.7438 |
| 0.147 | 4.1 | 3000 | 0.3965 | 15.8807 | 7.7145 |
| 0.1292 | 5.08 | 3500 | 0.4000 | 15.8587 | 7.7065 |
| 0.1187 | 6.05 | 4000 | 0.4029 | 15.7491 | 7.6398 |
| 0.1368 | 7.03 | 4500 | 0.4041 | 15.7600 | 7.6558 |
| 0.1231 | 8.0 | 5000 | 0.4041 | 15.7710 | 7.6691 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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