Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
bert-base-uncased-sentiment-model – AI Model by vincent-lpj | AlphaNeural AI
You can deploy this model and start earning money today!
vincent-lpj
/
bert-base-uncased-sentiment-model
like
0
transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
bert-base-uncased-sentiment-model
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2585
Accuracy: 0.9319
F1: 0.9322
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: 4
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.3242
1.0
2800
0.3422
0.9219
0.9206
0.1665
2.0
5600
0.2585
0.9319
0.9322
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
