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DistilBERT-finetuned-customer-queries-balanced – AI Model by SebaK13 | AlphaNeural AI
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DistilBERT-finetuned-customer-queries-balanced
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transformers
safetensors
distilbert
text-classification
generated_from_trainer
arrow
distilbert/distilbert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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DistilBERT-finetuned-customer-queries-balanced
This model is a fine-tuned version of
distilbert-base-uncased
on the arrow dataset. It achieves the following results on the evaluation set:
Loss: 0.0918
Accuracy: 0.99
F1: 0.9900
Precision: 0.9900
Recall: 0.99
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
Precision
Recall
1.2982
1.0
343
0.1717
0.988
0.9880
0.9881
0.988
0.1622
2.0
686
0.0918
0.99
0.9900
0.9900
0.99
Framework versions
Transformers 4.42.1
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
