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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:
- jindol/debugged_03_Whisper_datasets
model-index:
- name: repo_name
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. -->
# repo_name
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the debugged_03_Whisper_datasets dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6540
- Cer: 32.5714
## 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: Use 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0001 | 500.0 | 1000 | 1.4956 | 32.5714 |
| 0.0001 | 1000.0 | 2000 | 1.5831 | 36.0 |
| 0.0 | 1500.0 | 3000 | 1.6306 | 32.5714 |
| 0.0 | 2000.0 | 4000 | 1.6540 | 32.5714 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.0.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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