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eBERT_sa_cv_9_fold9 – AI Model by DiederikMartens | AlphaNeural AI
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DiederikMartens
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eBERT_sa_cv_9_fold9
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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eBERT_sa_cv_9_fold9
This model is a fine-tuned version of
google-bert/bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6573
F1: 0.5477
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: 4.47e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
F1
No log
1.0
325
0.5783
0.4430
0.6242
2.0
650
0.5236
0.5043
0.6242
3.0
975
0.6573
0.5477
Framework versions
Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
