whisper-small-gd – AI Model by joohwan | AlphaNeural AI

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whisper-small-gd

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whisper-small-gd

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1180
Wer: 14.2298

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: 2
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0723	0.09	250	0.2013	22.6924
0.044	0.18	500	0.1826	27.3905
0.1209	0.27	750	0.1705	27.2700
0.0973	0.36	1000	0.1462	15.1182
0.0941	0.45	1250	0.1322	15.6603
0.076	0.54	1500	0.1258	18.3557
0.0967	0.63	1750	0.1203	14.8020
0.0757	0.72	2000	0.1180	14.2298

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3