whisper-base-ro – AI Model by augustinjianu | AlphaNeural AI

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augustinjianu/
whisper-base-ro

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automatic-speech-recognition

generated_from_trainer

mozilla-foundation/common_voice_17_0

openai/whisper-base

endpoints_compatible

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Whisper Base Ro - Augustin Jianu

This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.4626
Wer: 31.0909

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: 5e-06
train_batch_size: 16
eval_batch_size: 8
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: 500
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.366	1.7730	1000	0.4236	35.2256
0.1676	3.5461	2000	0.3700	31.5503
0.0752	5.3191	3000	0.3683	30.3287
0.0355	7.0922	4000	0.3841	30.1756
0.025	8.8652	5000	0.4003	30.0011
0.0106	10.6383	6000	0.4232	31.6820
0.0067	12.4113	7000	0.4380	31.4221
0.0043	14.1844	8000	0.4520	30.1613
0.0038	15.9574	9000	0.4594	30.1079
0.0032	17.7305	10000	0.4626	31.0909

Framework versions

Transformers 4.48.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0