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---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- aihub_elder
model-index:
- name: whisper-small-ko-E50_Yfreq-SA
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-E50_Yfreq-SA
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub elder over 70 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1687
- Cer: 4.7169
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4395 | 0.13 | 100 | 0.2828 | 6.6494 |
| 0.2892 | 0.26 | 200 | 0.2139 | 6.1971 |
| 0.2647 | 0.39 | 300 | 0.2029 | 6.4673 |
| 0.2371 | 0.52 | 400 | 0.1935 | 5.5569 |
| 0.2442 | 0.64 | 500 | 0.1884 | 5.3513 |
| 0.2419 | 0.77 | 600 | 0.1828 | 5.3102 |
| 0.2159 | 0.9 | 700 | 0.1848 | 5.2103 |
| 0.1394 | 1.03 | 800 | 0.1771 | 5.1281 |
| 0.1337 | 1.16 | 900 | 0.1799 | 5.2925 |
| 0.1458 | 1.29 | 1000 | 0.1787 | 4.9283 |
| 0.1306 | 1.42 | 1100 | 0.1787 | 4.8637 |
| 0.1211 | 1.55 | 1200 | 0.1733 | 4.7991 |
| 0.1469 | 1.68 | 1300 | 0.1692 | 4.7227 |
| 0.1157 | 1.81 | 1400 | 0.1688 | 4.7404 |
| 0.1304 | 1.93 | 1500 | 0.1687 | 4.7169 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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