---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mangoo111/stt_datasets
model-index:
- name: AIHub_non-face-to-face-care_data_model
  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. -->

# AIHub_non-face-to-face-care_data_model

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the AIHub_non-face-to-face-care_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5251
- Cer: 91.7452
- Normalized Cer: 0.1147

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer      | Normalized Cer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 0.6825        | 2.5   | 1000 | 0.7206          | 125.5376 | 0.1569         |
| 0.4637        | 5.0   | 2000 | 0.4858          | 96.4728  | 0.1206         |
| 0.34          | 7.5   | 3000 | 0.4926          | 92.8792  | 0.1161         |
| 0.2378        | 10.0  | 4000 | 0.5251          | 91.7452  | 0.1147         |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1