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---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_finetune
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. -->
# whisper_finetune
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4807
- Cer: 14.7381
- Wer: 40.8215
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 0.2038 | 0.4 | 500 | 0.4405 | 13.6475 | 39.1975 |
| 0.1892 | 0.8 | 1000 | 0.4491 | 14.5230 | 40.5892 |
| 0.1218 | 1.2 | 1500 | 0.4710 | 14.4216 | 40.2519 |
| 0.1227 | 1.6 | 2000 | 0.4879 | 14.3981 | 40.1969 |
| 0.1311 | 2.0 | 2500 | 0.4638 | 14.6655 | 40.9614 |
| 0.0945 | 2.4 | 3000 | 0.4783 | 14.6635 | 40.9190 |
| 0.0874 | 2.8 | 3500 | 0.4743 | 14.3360 | 40.4492 |
| 0.0759 | 3.2 | 4000 | 0.4807 | 14.7381 | 40.8215 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
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