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DistilBERT-finetuned-customer-queries – AI Model by SebaK13 | AlphaNeural AI
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DistilBERT-finetuned-customer-queries
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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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DistilBERT-finetuned-customer-queries
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: 0.1443
Accuracy: 0.9935
F1: 0.9935
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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
1.6111
1.0
250
0.3456
0.9895
0.9895
0.264
2.0
500
0.1443
0.9935
0.9935
Framework versions
Transformers 4.42.1
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
