asr2_medium_v0.1 – AI Model by miosipof | AlphaNeural AI

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asr2_medium_v0.1

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openai/whisper-medium

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Whisper Medium

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

Loss: 0.8245
Wer: 69.1977
Cer: 45.5477

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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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_ratio: 0.4
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
4.2121	1.0	251	4.2340	150.7163	87.2603
1.0726	2.0	502	1.1107	79.9427	52.9288
0.8421	3.0	753	0.9359	203.4384	152.2721
0.6134	4.0	1004	0.8391	102.2923	77.7515
0.4891	5.0	1255	0.8245	69.1977	45.5477

Framework versions

PEFT 0.14.0
Transformers 4.48.3
Pytorch 2.2.0
Datasets 3.2.0
Tokenizers 0.21.0