This model is a fine-tuned version of openai/whisper-base on the AIHub_non-face-to-face-care_data dataset. It achieves the following results on the evaluation set:

Loss: 0.5251
Cer: 91.7452
Normalized Cer: 0.1147

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
0.6825	2.5	1000	0.7206	125.5376	0.1569
0.4637	5.0	2000	0.4858	96.4728	0.1206
0.34	7.5	3000	0.4926	92.8792	0.1161
0.2378	10.0	4000	0.5251	91.7452	0.1147

Framework versions

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

mangoo111/repo_name

AIHub_non-face-to-face-care_data_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mangoo111/
repo_name