wav2vec2-large-mms-1b-aft-mmc – AI Model by robertp408 | AlphaNeural AI

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robertp408/
wav2vec2-large-mms-1b-aft-mmc

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automatic-speech-recognition

generated_from_trainer

facebook/mms-1b-all

endpoints_compatible

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wav2vec2-large-mms-1b-aft-mmc

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

Loss: 1.3464
Wer: 0.6981

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: 2
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.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: 100
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
13.1415	0.5263	100	9.0823	1.2933
3.968	1.0526	200	3.8510	0.9984
3.4887	1.5789	300	3.2492	0.9984
1.9099	2.1053	400	1.8789	0.7918
1.5364	2.6316	500	1.5877	0.7513
1.3236	3.1579	600	1.5096	0.7653
1.2527	3.6842	700	1.3780	0.7131
1.1843	4.2105	800	1.3713	0.7081
1.1542	4.7368	900	1.3464	0.6981

Framework versions

Transformers 4.57.0
Pytorch 2.8.0+cu128
Datasets 4.1.1
Tokenizers 0.22.1