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roberta-finetuned-ner – AI Model by kSaluja | AlphaNeural AI
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kSaluja
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roberta-finetuned-ner
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transformers
pytorch
tensorboard
xlm-roberta
token-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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roberta-finetuned-ner
This model is a fine-tuned version of
xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.1322
Precision: 0.9772
Recall: 0.9782
F1: 0.9777
Accuracy: 0.9767
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
253
0.1694
0.9636
0.9555
0.9595
0.9617
0.4479
2.0
506
0.1374
0.9743
0.9762
0.9752
0.9743
0.4479
3.0
759
0.1322
0.9772
0.9782
0.9777
0.9767
Framework versions
Transformers 4.17.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6
