---
language:
- hi
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
model-index:
- name: Whisper Small ko-Yfreq-E - syp1229
  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-Yfreq-E - syp1229

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aihub Y E dialogue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2157
- Cer: 0.0491

## 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: 2e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2455        | 0.3   | 100  | 0.2528          | 0.0663 |
| 0.2591        | 0.59  | 200  | 0.2452          | 0.0646 |
| 0.1702        | 0.89  | 300  | 0.2298          | 0.0628 |
| 0.0738        | 1.19  | 400  | 0.2136          | 0.0923 |
| 0.0957        | 1.48  | 500  | 0.2263          | 0.0618 |
| 0.0729        | 1.78  | 600  | 0.2139          | 0.0565 |
| 0.0242        | 2.07  | 700  | 0.2073          | 0.0520 |
| 0.028         | 2.37  | 800  | 0.2063          | 0.0482 |
| 0.0351        | 2.67  | 900  | 0.2162          | 0.0506 |
| 0.0239        | 2.96  | 1000 | 0.2075          | 0.0513 |
| 0.0088        | 3.26  | 1100 | 0.2194          | 0.0495 |
| 0.0079        | 3.56  | 1200 | 0.2187          | 0.0508 |
| 0.0072        | 3.85  | 1300 | 0.2217          | 0.0510 |
| 0.0046        | 4.15  | 1400 | 0.2164          | 0.0488 |
| 0.0038        | 4.44  | 1500 | 0.2149          | 0.0490 |
| 0.003         | 4.74  | 1600 | 0.2157          | 0.0491 |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3