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---
library_name: transformers
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_adult_baseline
model-index:
- name: whisper-small-ko-baseline
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-small-ko-baseline
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub adult speed changed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2914
- Cer: 8.5820
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 50
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.2433 | 0.1289 | 100 | 0.2943 | 7.8712 |
| 0.1379 | 0.2579 | 200 | 0.2758 | 7.4248 |
| 0.1105 | 0.3868 | 300 | 0.2831 | 7.6010 |
| 0.1231 | 0.5158 | 400 | 0.2671 | 7.2192 |
| 0.0984 | 0.6447 | 500 | 0.2721 | 7.2603 |
| 0.0938 | 0.7737 | 600 | 0.2742 | 7.1840 |
| 0.0954 | 0.9026 | 700 | 0.2718 | 6.9901 |
| 0.0385 | 1.0316 | 800 | 0.2649 | 6.9549 |
| 0.0302 | 1.1605 | 900 | 0.2645 | 7.5129 |
| 0.0388 | 1.2895 | 1000 | 0.2722 | 7.0606 |
| 0.0338 | 1.4184 | 1100 | 0.2819 | 7.8889 |
| 0.0389 | 1.5474 | 1200 | 0.2725 | 7.7479 |
| 0.0335 | 1.6763 | 1300 | 0.2716 | 8.3647 |
| 0.0331 | 1.8053 | 1400 | 0.2751 | 7.6774 |
| 0.0343 | 1.9342 | 1500 | 0.2825 | 7.8008 |
| 0.0134 | 2.0632 | 1600 | 0.2739 | 6.9079 |
| 0.0127 | 2.1921 | 1700 | 0.2779 | 8.8287 |
| 0.0141 | 2.3211 | 1800 | 0.2822 | 7.1429 |
| 0.0113 | 2.4500 | 1900 | 0.2864 | 8.6407 |
| 0.0131 | 2.5790 | 2000 | 0.2797 | 10.5909 |
| 0.0103 | 2.7079 | 2100 | 0.2835 | 8.4880 |
| 0.0117 | 2.8369 | 2200 | 0.2828 | 11.5425 |
| 0.0116 | 2.9658 | 2300 | 0.2832 | 9.5747 |
| 0.0046 | 3.0948 | 2400 | 0.2862 | 8.8640 |
| 0.0045 | 3.2237 | 2500 | 0.2877 | 10.0388 |
| 0.0061 | 3.3527 | 2600 | 0.2886 | 8.9991 |
| 0.0055 | 3.4816 | 2700 | 0.2894 | 8.4704 |
| 0.0052 | 3.6106 | 2800 | 0.2904 | 8.4410 |
| 0.0059 | 3.7395 | 2900 | 0.2908 | 10.3266 |
| 0.0051 | 3.8685 | 3000 | 0.2913 | 9.3280 |
| 0.0047 | 3.9974 | 3100 | 0.2914 | 8.5820 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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