whisper-tiny-rus – AI Model by constantinedivis | AlphaNeural AI

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constantinedivis/
whisper-tiny-rus

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automatic-speech-recognition

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openai/whisper-tiny

endpoints_compatible

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whisper-tiny-rus

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4508
Wer: 37.6577

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: 128
eval_batch_size: 128
seed: 42
optimizer: Use 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: 600
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6166	0.3984	100	0.6163	45.3709
0.5109	0.7968	200	0.5225	41.1251
0.4615	1.1952	300	0.4850	39.6391
0.4377	1.5936	400	0.4664	38.5069
0.433	1.9920	500	0.4544	37.6695
0.4186	2.3904	600	0.4508	37.6577

Framework versions

Transformers 4.49.0
Pytorch 2.1.0+cu118
Datasets 3.4.0
Tokenizers 0.21.1