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mms_gn_fine_tune – AI Model by kunhanw | AlphaNeural AI
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mms_gn_fine_tune
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
common_voice_13_0
facebook/mms-1b-all
finetune
cc-by-nc-4.0
model-index
endpoints_compatible
us
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mms_gn_fine_tune
This model is a fine-tuned version of
facebook/mms-1b-all
on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
Loss: 0.1811
Wer: 0.3291
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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
7.0552
1.79
100
0.2300
0.3880
0.2259
3.57
200
0.1811
0.3291
Framework versions
Transformers 4.35.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
