v3_Large – AI Model by deepinfinityai | AlphaNeural AI

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deepinfinityai/
v3_Large

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automatic-speech-recognition

generated_from_trainer

deepinfinityai/11_audios_dataset

openai/whisper-medium

endpoints_compatible

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Whisper Large Medical(11)

This model is a fine-tuned version of openai/whisper-medium on the 11 Sentences dataset. It achieves the following results on the evaluation set:

Loss: 0.8179
Wer: 35.7143

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: 4
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: 50
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.5756	25.0	50	0.0563	7.1429
0.0009	50.0	100	0.0505	0.0
0.0001	75.0	150	0.0694	0.0
0.0001	100.0	200	0.1348	0.0
0.0001	125.0	250	0.2494	0.0
0.0	150.0	300	0.3976	0.0
0.0	175.0	350	0.5560	7.1429
0.0	200.0	400	0.6852	35.7143
0.0	225.0	450	0.7813	35.7143
0.0	250.0	500	0.8179	35.7143

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0