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wav2vec2-large-mms-1b-ngn-on-bam-colab – AI Model by bomolopuu | AlphaNeural AI
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wav2vec2-large-mms-1b-ngn-on-bam-colab
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/mms-1b-all
finetune
cc-by-nc-4.0
endpoints_compatible
us
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wav2vec2-large-mms-1b-ngn-on-bam-colab
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: 1.0502
Wer: 0.65
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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use 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_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
5.8957
9.0952
100
1.0502
0.65
Framework versions
Transformers 4.48.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.21.0
