---
language:
- ko
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- nicekevin/lgevr_sentence_v2_tmp
model-index:
- name: nicekevin/whisper_bs_ft_lgevr2_v3_2
  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. -->

# nicekevin/whisper_bs_ft_lgevr2_v3_2

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the lgevr_sentence_v2 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.4283
- eval_cer: 12.9976
- eval_runtime: 10.4189
- eval_samples_per_second: 3.743
- eval_steps_per_second: 0.48
- epoch: 25.0
- step: 500

## 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-06
- 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: 2000
- mixed_precision_training: Native AMP

### Framework versions

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