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---
library_name: transformers
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- hyk000/woerae
model-index:
- name: wr_md
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. -->
# wr_md
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the wr_ds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4690
- Cer: 32.7677
## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2600
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7558 | 3.8462 | 1000 | 1.0555 | 65.3794 |
| 0.0785 | 7.6923 | 2000 | 0.4690 | 32.7677 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.0
- Datasets 3.0.2
- Tokenizers 0.20.1
|