Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
distilbert-base-product-related – AI Model by junmeng-sf | AlphaNeural AI
You can deploy this model and start earning money today!
junmeng-sf
/
distilbert-base-product-related
like
0
peft
safetensors
distilbert
text-classification
adapter
lora
transformers
distilbert/distilbert-base-uncased
adapter
apache-2.0
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
distilbert-base-product-related
This model is a fine-tuned version of
distilbert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0662
Accuracy: 0.9813
Precision: 0.9733
Recall: 0.9904
F1: 0.9818
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: 16
eval_batch_size: 16
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.1412
1.0
3360
0.0914
0.9690
0.9586
0.9816
0.9700
0.0596
2.0
6720
0.0699
0.9798
0.9708
0.9901
0.9804
0.0702
3.0
10080
0.0662
0.9813
0.9733
0.9904
0.9818
Framework versions
PEFT 0.17.1
Transformers 4.55.4
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.21.4
