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wav2vec2-base-language-classification-en-hi-ta – AI Model by ar5entum | AlphaNeural AI
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ar5entum
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wav2vec2-base-language-classification-en-hi-ta
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transformers
tensorboard
safetensors
wav2vec2
audio-classification
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2-base-lang-id
This model is a fine-tuned version of
facebook/wav2vec2-base
on the /content/dataset dataset. It achieves the following results on the evaluation set:
Loss: 0.0134
Accuracy: 0.998
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: 4e-05
train_batch_size: 24
eval_batch_size: 4
seed: 0
distributed_type: multi-GPU
gradient_accumulation_steps: 2
total_train_batch_size: 48
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
lr_scheduler_warmup_steps: 200
num_epochs: 5.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0677
1.0
601
0.0297
0.9935
0.0345
2.0
1202
0.0362
0.9935
0.013
3.0
1803
0.0151
0.997
0.0003
4.0
2404
0.0134
0.998
0.0003
4.9925
3000
0.0127
0.998
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
