---
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-E30_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-E30_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: 0.1771
- Cer: 5.1809

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4152        | 0.13  | 100  | 0.2871          | 6.9196 |
| 0.2698        | 0.26  | 200  | 0.2207          | 6.1208 |
| 0.224         | 0.39  | 300  | 0.2093          | 5.8212 |
| 0.2407        | 0.52  | 400  | 0.2063          | 5.6802 |
| 0.234         | 0.64  | 500  | 0.1976          | 6.4556 |
| 0.2168        | 0.77  | 600  | 0.1901          | 5.3924 |
| 0.1846        | 0.9   | 700  | 0.1891          | 5.4159 |
| 0.1231        | 1.03  | 800  | 0.1823          | 5.1574 |
| 0.1159        | 1.16  | 900  | 0.1880          | 5.2749 |
| 0.1239        | 1.29  | 1000 | 0.1860          | 5.1809 |
| 0.1207        | 1.42  | 1100 | 0.1834          | 5.6273 |
| 0.101         | 1.55  | 1200 | 0.1788          | 5.5569 |
| 0.1193        | 1.68  | 1300 | 0.1771          | 5.0811 |
| 0.0949        | 1.81  | 1400 | 0.1775          | 5.1868 |
| 0.1181        | 1.93  | 1500 | 0.1771          | 5.1809 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0