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---
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 v1 - Shiv Kumar Ganesh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: vi
split: test
args: vi
metrics:
- name: Wer
type: wer
value: 34.09738977846019
---
<!-- 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 v1 - Shiv Kumar Ganesh
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0641
- Wer: 34.0974
## 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: 7000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0005 | 31.0 | 500 | 0.7179 | 33.7464 |
| 0.0002 | 62.0 | 1000 | 0.7837 | 32.4742 |
| 0.0001 | 93.0 | 1500 | 0.8267 | 34.2729 |
| 0.0001 | 124.0 | 2000 | 0.8677 | 35.1722 |
| 0.0 | 156.0 | 2500 | 0.9045 | 35.3257 |
| 0.0 | 187.0 | 3000 | 0.9316 | 33.9877 |
| 0.0 | 218.0 | 3500 | 0.9585 | 34.0097 |
| 0.0 | 249.0 | 4000 | 0.9846 | 33.3626 |
| 0.0 | 281.0 | 4500 | 1.0082 | 33.4832 |
| 0.0 | 312.0 | 5000 | 1.0247 | 33.7026 |
| 0.0 | 343.0 | 5500 | 1.0391 | 32.8691 |
| 0.0 | 374.0 | 6000 | 1.0516 | 32.9020 |
| 0.0 | 406.0 | 6500 | 1.0606 | 33.6477 |
| 0.0 | 437.0 | 7000 | 1.0641 | 34.0974 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
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