wh – AI Model by mehdipakdel | AlphaNeural AI

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mehdipakdel/
wh

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automatic-speech-recognition

generated_from_trainer

MohammadGholizadeh/fleurs-farsi

openai/whisper-small

endpoints_compatible

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Whisper Small Persian

This model is a fine-tuned version of openai/whisper-small on the Fleurs Farsi dataset. It achieves the following results on the evaluation set:

Loss: 0.3818
Wer: 25.8171

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: 3e-05
train_batch_size: 32
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3277	2.0	50	0.3894	34.8873
0.1146	4.0	100	0.3268	28.6293
0.0373	6.0	150	0.3289	27.3372
0.0142	8.0	200	0.3390	27.5399
0.0036	10.0	250	0.3523	26.5265
0.0024	12.0	300	0.3677	26.5265
0.001	14.0	350	0.3734	26.5011
0.0007	16.0	400	0.3777	26.1971
0.0007	18.0	450	0.3807	25.9944
0.0006	20.0	500	0.3818	25.8171

Framework versions

Transformers 4.48.0
Pytorch 2.8.0+cu126
Datasets 4.1.1
Tokenizers 0.21.4