transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer hi dataset:aihub_elder base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
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-E2
  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-E2

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: 0.1664
- Cer: 4.4232

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.319         | 0.13  | 100  | 0.2515          | 6.9431 |
| 0.2959        | 0.26  | 200  | 0.2258          | 6.1501 |
| 0.3025        | 0.39  | 300  | 0.2085          | 5.5275 |
| 0.2603        | 0.52  | 400  | 0.2091          | 5.5334 |
| 0.2436        | 0.64  | 500  | 0.1952          | 5.3454 |
| 0.2213        | 0.77  | 600  | 0.1903          | 5.0282 |
| 0.2142        | 0.9   | 700  | 0.1836          | 5.0811 |
| 0.1257        | 1.03  | 800  | 0.1783          | 6.0973 |
| 0.0992        | 1.16  | 900  | 0.1745          | 4.6640 |
| 0.1092        | 1.29  | 1000 | 0.1832          | 5.7390 |
| 0.1134        | 1.42  | 1100 | 0.1754          | 5.0458 |
| 0.093         | 1.55  | 1200 | 0.1731          | 4.5348 |
| 0.1194        | 1.68  | 1300 | 0.1671          | 4.2822 |
| 0.1016        | 1.81  | 1400 | 0.1687          | 4.3997 |
| 0.1002        | 1.93  | 1500 | 0.1759          | 6.1031 |
| 0.0374        | 2.06  | 1600 | 0.1702          | 4.6464 |
| 0.0404        | 2.19  | 1700 | 0.1695          | 4.8696 |
| 0.0374        | 2.32  | 1800 | 0.1712          | 4.5230 |
| 0.039         | 2.45  | 1900 | 0.1673          | 4.2234 |
| 0.0404        | 2.58  | 2000 | 0.1671          | 4.5406 |
| 0.0422        | 2.71  | 2100 | 0.1653          | 4.3057 |
| 0.032         | 2.84  | 2200 | 0.1683          | 4.8755 |
| 0.0329        | 2.97  | 2300 | 0.1657          | 3.9944 |
| 0.0119        | 3.09  | 2400 | 0.1687          | 4.0942 |
| 0.0143        | 3.22  | 2500 | 0.1676          | 4.2704 |
| 0.0119        | 3.35  | 2600 | 0.1687          | 4.2822 |
| 0.011         | 3.48  | 2700 | 0.1714          | 4.2939 |
| 0.0111        | 3.61  | 2800 | 0.1657          | 4.3527 |
| 0.0124        | 3.74  | 2900 | 0.1661          | 4.2058 |
| 0.0123        | 3.87  | 3000 | 0.1662          | 4.4114 |
| 0.0127        | 4.0   | 3100 | 0.1664          | 4.4232 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
