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mms-zul-finetuned – AI Model by amanuelbyte | AlphaNeural AI
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mms-zul-finetuned
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transformers
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
generator
facebook/mms-1b-all
finetune
cc-by-nc-4.0
model-index
endpoints_compatible
us
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mms-zul-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: 0.1072
Wer: 0.1908
Cer: 0.0260
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: 50
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
1.0437
0.7105
100
0.1440
0.2392
0.0338
0.7657
1.0
141
0.1072
0.1908
0.0260
Framework versions
Transformers 5.5.4
Pytorch 2.7.1+cu118
Datasets 4.8.4
Tokenizers 0.22.2
