metadata
language:
- vi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium VI - CV - Augmented
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: vi
split: test
args: vi
metrics:
- type: wer
value: 18.030269796007897
name: Wer
- type: wer
value: 17.98
name: WER
- type: cer
value: 8.31
name: CER
Whisper Medium VI - CV - Augmented
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6613
- Wer: 18.0303
- Cer: 8.3095
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 |
|---|---|---|---|---|---|
| 0.0053 | 11.49 | 1000 | 0.5429 | 18.1290 | 8.4643 |
| 0.0021 | 22.99 | 2000 | 0.5916 | 18.8857 | 8.6538 |
| 0.0001 | 34.48 | 3000 | 0.6348 | 18.3374 | 8.4296 |
| 0.0001 | 45.98 | 4000 | 0.6508 | 17.9754 | 8.3149 |
| 0.0001 | 57.47 | 5000 | 0.6613 | 18.0303 | 8.3095 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2