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wav2vec2_milDB – AI Model by AdaCodruta | AlphaNeural AI
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wav2vec2_milDB
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transformers
tensorboard
safetensors
wav2vec2
automatic-speech-recognition
generated_from_trainer
facebook/wav2vec2-base
finetune
apache-2.0
endpoints_compatible
us
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wav2vec2_milDB
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.6994
Wer: 1.0
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: 0.0001
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: 500
training_steps: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
2.0257
10.9890
1000
1.6873
1.0
1.0671
21.9780
2000
1.6131
1.0
2.4045
32.9670
3000
2.6980
1.0
2.5542
43.9560
4000
2.7001
1.0
2.5504
54.9451
5000
2.6994
1.0
Framework versions
Transformers 4.40.2
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.19.1
