whisper-large-v3-cv17-dv – AI Model by alakxender | AlphaNeural AI

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alakxender/
whisper-large-v3-cv17-dv

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automatic-speech-recognition

generated_from_trainer

mozilla-foundation/common_voice_17_0

openai/whisper-large-v3

endpoints_compatible

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This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4610
Wer: 71.0345

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: 16
eval_batch_size: 36
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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.4644	0.9772	300	1.0654	203.9655
0.2384	1.9544	600	0.3342	84.8276
0.1481	2.9316	900	0.2715	78.7931
0.0975	2.9772	1200	0.2635	76.0345
0.0616	3.9544	1500	0.2841	73.1034
0.0399	4.9772	1800	0.3215	72.2414
0.0218	5.9772	2100	0.3881	73.7931
0.046	6.9772	2400	0.2772	74.1379
0.018	7.9544	2700	0.3344	71.3793
0.0067	8.9316	3000	0.3947	71.7241
0.0023	9.9088	3300	0.4246	72.5862
0.0008	10.8860	3600	0.4503	71.7241
0.0003	11.8632	3900	0.4610	71.0345

Framework versions

Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.0
Tokenizers 0.19.1