transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko dataset:k-seungri/k_whisper_dataset 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:
- k-seungri/k_whisper_dataset
base_model: openai/whisper-base
model-index:
- name: k-seungri/k_whisper_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# k-seungri/k_whisper_model

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the k_whisper_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6590
- Cer: 53.0478

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0002        | 142.86 | 1000 | 0.5964          | 16.9687 |
| 0.0001        | 285.71 | 2000 | 0.6299          | 16.6392 |
| 0.0001        | 428.57 | 3000 | 0.6459          | 17.1334 |
| 0.0001        | 571.43 | 4000 | 0.6590          | 53.0478 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
