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Multiple_Labels – AI Model by thanhcong2001 | AlphaNeural AI
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thanhcong2001
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Multiple_Labels
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Multiple_Labels
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8555
Acc: 0.6609
F1: 0.6545
Recall: 0.6609
Precision: 0.6557
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 0.5
Training results
Training Loss
Epoch
Step
Validation Loss
Acc
F1
Recall
Precision
0.8388
0.5
2801
0.8555
0.6609
0.6545
0.6609
0.6557
Framework versions
Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0
