mms-amh-finetuned – AI Model by amanuelbyte | AlphaNeural AI

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amanuelbyte/
mms-amh-finetuned

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automatic-speech-recognition

generated_from_trainer

facebook/mms-1b-all

endpoints_compatible

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mms-amh-finetuned

This model is a fine-tuned version of facebook/mms-1b-all on the generator dataset. It achieves the following results on the evaluation set:

Loss: 0.2463
Wer: 0.1681
Cer: 0.0487

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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use OptimizerNames.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: 99
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
2.0536	0.5964	198	0.4753	0.3800	0.1057
1.7597	1.1928	396	0.3566	0.2586	0.0729
1.4389	1.7892	594	0.3160	0.2259	0.0634
1.2412	2.3855	792	0.2711	0.1872	0.0538
0.9865	2.9819	990	0.2463	0.1681	0.0487
0.9865	3.0	996	0.2459	0.1682	0.0487

Framework versions

Transformers 5.5.4
Pytorch 2.7.1+cu118
Datasets 4.8.4
Tokenizers 0.22.2