metadata

library_name: transformers
language:
  - ko
license: apache-2.0
base_model: morish/whisper-medium-ko-v0_1_1
tags:
  - morish/kresp_speech_87_48278_150000
  - morish/open_communication_109_48652_150000
  - morish/senior_kspeech_107_150000
  - morish/telemedicine_208_150000_200000
  - morish/welfare_470_150000_200000
  - whisper-2024-09-06
  - generated_from_trainer
model-index:
  - name: whisper-ko-finetune
    results: []

whisper-ko-finetune

This model is a fine-tuned version of morish/whisper-medium-ko-v0_1_1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0829
Cer: 2.4784

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-06
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.01
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.0868	0.2385	500	0.0859	2.5607
0.0856	0.4770	1000	0.0843	2.5300
0.0875	0.7155	1500	0.0833	2.4804
0.0815	0.9540	2000	0.0829	2.4784

Framework versions

Transformers 4.44.2
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1