test_mms – AI Model by oluwagbotty | AlphaNeural AI

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oluwagbotty/
test_mms

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automatic-speech-recognition

generated_from_trainer

facebook/mms-1b-all

endpoints_compatible

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test_mms

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: 0.8774
Wer: 0.5800

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 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: 100
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8977	3.128	100	0.9470	0.6404
0.7768	6.256	200	0.9301	0.5731
0.685	9.384	300	0.8985	0.5986
0.6113	12.512	400	0.8818	0.5708
0.5605	15.64	500	0.8921	0.5568
0.5259	18.768	600	0.8774	0.5800

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1