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wav2vec2-nepali-rikeshsilwal – AI Model by RikeshSilwal | AlphaNeural AI
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RikeshSilwal
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wav2vec2-nepali-rikeshsilwal
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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wav2vec2-nepali-rikeshsilwal
This model is a fine-tuned version of
facebook/wav2vec2-large-xlsr-53
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3282
Wer: 0.4024
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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 50
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2477
17.09
1000
0.2943
0.4475
0.0974
34.19
2000
0.3282
0.4024
Framework versions
Transformers 4.28.0
Pytorch 2.1.0+cu121
Datasets 1.18.0
Tokenizers 0.13.3
