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roberta-large-finetuned-ner – AI Model by PSI-PAIRC | AlphaNeural AI
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PSI-PAIRC
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roberta-large-finetuned-ner
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transformers
pytorch
tensorboard
safetensors
roberta
token-classification
generated_from_trainer
klue/roberta-large
finetune
autotrain_compatible
endpoints_compatible
us
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roberta-large-finetuned-ner
This model is a fine-tuned version of
klue/roberta-large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0290
Precision: 0.9626
Recall: 0.9588
F1: 0.9607
Accuracy: 0.9936
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: 2
eval_batch_size: 2
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
0.0682
1.0
1240
0.0561
0.9327
0.9392
0.9359
0.9898
0.0359
2.0
2480
0.0408
0.9701
0.9539
0.9619
0.9939
0.0157
3.0
3720
0.0290
0.9626
0.9588
0.9607
0.9936
Framework versions
Transformers 4.31.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.13.2.dev0
Tokenizers 0.13.3
