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bert-finetuned-sem_eval-english – AI Model by rbc33 | AlphaNeural AI
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rbc33
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bert-finetuned-sem_eval-english
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transformers
safetensors
bert
text-classification
generated_from_trainer
sem_eval_2018_task_1
google-bert/bert-base-uncased
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-sem_eval-english
This model is a fine-tuned version of
bert-base-uncased
on the sem_eval_2018_task_1 dataset. It achieves the following results on the evaluation set:
Loss: 0.3283
F1: 0.6578
Roc Auc: 0.7603
Accuracy: 0.2483
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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
F1
Roc Auc
Accuracy
0.408
1.0
855
0.3283
0.6578
0.7603
0.2483
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu124
Datasets 2.15.0
Tokenizers 0.20.3
