whisper-tiny-zh_CN_lr4_lowdata – AI Model by VingeNie | AlphaNeural AI

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VingeNie/
whisper-tiny-zh_CN_lr4_lowdata

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automatic-speech-recognition

generated_from_trainer

mozilla-foundation/common_voice_16_1

openai/whisper-tiny

endpoints_compatible

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Whisper Tiny chinese - VingeNie

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

Loss: 0.7976
Cer Ortho: 35.9855
Cer: 29.9636

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 25
training_steps: 1500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer Ortho	Cer
0.8364	1.0	300	0.8423	44.8697	32.3523
0.5618	2.0	600	0.7816	44.3497	31.3998
0.3559	3.0	900	0.7747	41.4869	30.1052
0.2016	4.0	1200	0.7828	37.2903	30.2107
0.0953	5.0	1500	0.7976	35.9855	29.9636

Framework versions

Transformers 4.40.1
Pytorch 2.0.1+cu118
Datasets 2.19.0
Tokenizers 0.19.1