transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko base_model:openai/whisper-base license:apache-2.0 endpoints_compatible region:us
---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_finetune
  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_finetune

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3508
- Cer: 12.0915
- Wer: 35.6445

## 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: 32
- eval_batch_size: 16
- 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 | Cer     | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:|
| 0.3416        | 0.32  | 500  | 12.9022 | 0.3510          | 36.6764 |
| 0.3344        | 0.64  | 1000 | 12.7008 | 0.3562          | 36.9463 |
| 0.3119        | 0.96  | 1500 | 12.4164 | 0.3517          | 36.5065 |
| 0.246         | 1.28  | 2000 | 12.4510 | 0.3569          | 36.4665 |
| 0.2437        | 1.6   | 2500 | 12.0823 | 0.3487          | 36.0543 |
| 0.2318        | 1.92  | 3000 | 0.3454  | 11.9698         | 35.7519 |
| 0.1861        | 2.24  | 3500 | 0.3501  | 11.9882         | 35.6895 |
| 0.1729        | 2.56  | 4000 | 0.3508  | 12.0915         | 35.6445 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0
