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mms_que_gn_fine_tune – AI Model by kunhanw | AlphaNeural AI
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mms_que_gn_fine_tune
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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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mms_que_gn_fine_tune
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: 0.2604
Wer: 0.5340
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: 20
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
7.2571
0.85
100
0.3938
0.6438
0.2939
1.71
200
0.2993
0.5681
0.2564
2.56
300
0.2752
0.5377
0.2235
3.42
400
0.2604
0.5340
Framework versions
Transformers 4.35.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
