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distilhubert-finetuned-mixed-data – AI Model by A-POR-LOS-8000 | AlphaNeural AI
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A-POR-LOS-8000
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distilhubert-finetuned-mixed-data
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transformers
tensorboard
safetensors
hubert
audio-classification
generated_from_trainer
ntu-spml/distilhubert
finetune
apache-2.0
endpoints_compatible
us
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distilhubert-finetuned-mixed-data
This model is a fine-tuned version of
ntu-spml/distilhubert
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8806
Accuracy: 0.7912
F1: 0.7772
Precision: 0.8022
Recall: 0.7912
Confusion Matrix: [[59, 1, 1, 2], [20, 35, 22, 0], [2, 7, 68, 0], [2, 0, 0, 54]]
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: 0.0005
train_batch_size: 128
eval_batch_size: 128
seed: 123
gradient_accumulation_steps: 2
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_ratio: 0.1
num_epochs: 40
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
Confusion Matrix
0.4221
22.2222
100
0.8806
0.7912
0.7772
0.8022
0.7912
[[59, 1, 1, 2], [20, 35, 22, 0], [2, 7, 68, 0], [2, 0, 0, 54]]
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Tokenizers 0.19.1
