transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko dataset:mangoo111/stt_datasets_mixed base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mangoo111/stt_datasets_mixed
base_model: openai/whisper-base
model-index:
- name: AIHub_non-face-to-face-care_data_model_synthesis
  results: []
---

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# AIHub_non-face-to-face-care_data_model_synthesis

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: 0.4661
- Cer: 86.6106
- Normalized Cer: 0.1083

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
| 0.6939        | 2.5   | 1000 | 0.7123          | 100.3264 | 0.1254         |
| 0.4626        | 5.0   | 2000 | 0.4787          | 93.8130  | 0.1173         |
| 0.3828        | 7.5   | 3000 | 0.4661          | 86.6106  | 0.1083         |
| 0.3207        | 10.0  | 4000 | 0.4811          | 99.8114  | 0.1248         |


### Framework versions

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