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---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- AIHub
model-index:
- name: test
results: []
---
<!-- 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. -->
# test
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co./openai/whisper-base) on the Voice data of foreigners speaking Korean for AI learning dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5779
- Cer: 109.5803
## 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: 16
- eval_batch_size: 8
- 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6116 | 18.87 | 1000 | 3.5567 | 125.3727 |
| 0.014 | 37.74 | 2000 | 4.2442 | 100.9801 |
| 0.0027 | 56.6 | 3000 | 4.5135 | 104.3898 |
| 0.0019 | 75.47 | 4000 | 4.5779 | 109.5803 |
### Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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