jeju_stt_v2 / README.md
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---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-base
datasets:
- rlaorrn/working
model-index:
- name: jeju_stt
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. -->
# jeju_stt
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the jeju_audio dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3820
- Cer: 12.0409
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3689 | 2.0 | 1000 | 0.3853 | 13.4054 |
| 0.1884 | 4.0 | 2000 | 0.3488 | 11.9817 |
| 0.1059 | 6.0 | 3000 | 0.3607 | 11.9350 |
| 0.0634 | 8.0 | 4000 | 0.3820 | 12.0409 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1