mms_sesame_knn_vc – AI Model by resproj007 | AlphaNeural AI

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resproj007/
mms_sesame_knn_vc

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automatic-speech-recognition

generated_from_trainer

facebook/mms-1b-all

endpoints_compatible

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mms_sesame_knn_vc

This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.9116
Wer: 0.5995
Cer: 0.3471
Bertscore Precision: 0.6224
Bertscore Recall: 0.6664
Bertscore F1: 0.6400

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: 0.001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use adamw_torch_fused 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: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer	Bertscore Precision	Bertscore Recall	Bertscore F1
1.9216	21.0085	500	1.6593	0.5909	0.3361	0.6275	0.6691	0.6440
1.7172	43.0055	1000	1.7099	0.6058	0.3503	0.6315	0.6703	0.6469
1.302	65.0025	1500	1.7937	0.5971	0.3442	0.6320	0.6731	0.6484
1.0859	86.011	2000	1.9116	0.5995	0.3471	0.6224	0.6664	0.6400

Framework versions

Transformers 4.57.6
Pytorch 2.8.0+cu128
Datasets 4.5.0
Tokenizers 0.22.2