whisper-medium-ar – AI Model by arbml | AlphaNeural AI

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whisper-medium-ar

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openai/whisper-medium

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

Loss: 0.8488
Wer: 16.5882

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: 32
eval_batch_size: 16
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: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2963	0.1	1000	0.9115	27.3641
0.2676	0.2	2000	0.8796	24.1024
0.3166	0.3	3000	0.8467	20.1700
0.2797	0.4	4000	0.8756	29.4889
0.2302	0.5	5000	0.8523	19.6414
0.2803	0.6	6000	0.8715	19.7413
0.2794	0.7	7000	0.8548	18.6840
0.2173	0.8	8000	0.8543	17.9019
0.217	0.9	9000	0.8518	16.3840
0.1718	1.0	10000	0.8488	16.5882

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2