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wav2vec2-base-finetuned-ks – AI Model by oyamat | AlphaNeural AI
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wav2vec2-base-finetuned-ks
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transformers
tensorboard
safetensors
wav2vec2
audio-classification
generated_from_trainer
audiofolder
facebook/wav2vec2-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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wav2vec2-base-finetuned-ks
This model is a fine-tuned version of
facebook/wav2vec2-base
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.0015
Accuracy: 0.9997
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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use OptimizerNames.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
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0069
1.0
421
0.0040
0.9994
0.0075
2.0
842
0.0122
0.9966
0.0003
3.0
1263
0.0049
0.9994
0.0003
4.0
1684
0.0032
0.9994
0.0001
5.0
2105
0.0015
0.9997
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 2.11.0
Tokenizers 0.21.0
