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bert-finetuned-ner-sumups – AI Model by Shabeeb | AlphaNeural AI
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bert-finetuned-ner-sumups
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ner-sumups
This model is a fine-tuned version of
bert-base-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.9498
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.2605
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: 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
Precision
Recall
F1
Accuracy
No log
1.0
2
2.0593
0.0
0.0
0.0
0.2347
No log
2.0
4
1.9693
0.0
0.0
0.0
0.2632
No log
3.0
6
1.9498
0.0
0.0
0.0
0.2605
Framework versions
Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2
