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---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper Base Korean
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 ko
type: mozilla-foundation/common_voice_16_0
config: ko
split: test
args: ko
metrics:
- name: Wer
type: wer
value: 45.5026455026455
---
<!-- 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 Base Korean
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_0 ko dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6687
- Wer: 45.5026
## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.0149 | 133.0 | 1000 | 0.6687 | 45.5026 |
| 0.0048 | 266.0 | 2000 | 0.7148 | 47.7633 |
| 0.0024 | 399.0 | 3000 | 0.7484 | 48.4848 |
| 0.0014 | 533.0 | 4000 | 0.7774 | 49.0139 |
| 0.0009 | 666.0 | 5000 | 0.8037 | 48.8215 |
| 0.0006 | 799.0 | 6000 | 0.8269 | 49.4468 |
| 0.0004 | 933.0 | 7000 | 0.8482 | 49.3987 |
| 0.0003 | 1066.0 | 8000 | 0.8662 | 54.6417 |
| 0.0003 | 1199.0 | 9000 | 0.8800 | 49.9278 |
| 0.0003 | 1333.0 | 10000 | 0.8856 | 49.8316 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
|