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IceBERT-finetuned-ner – AI Model by ueb1 | AlphaNeural AI
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IceBERT-finetuned-ner
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transformers
pytorch
tensorboard
roberta
token-classification
generated_from_trainer
mim_gold_ner
gpl-3.0
model-index
autotrain_compatible
endpoints_compatible
us
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IceBERT-finetuned-ner
This model is a fine-tuned version of
vesteinn/IceBERT
on the mim_gold_ner dataset. It achieves the following results on the evaluation set:
Loss: 0.0799
Precision: 0.8927
Recall: 0.8649
F1: 0.8786
Accuracy: 0.9853
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: 16
eval_batch_size: 16
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
0.0528
1.0
2904
0.0774
0.8784
0.8529
0.8655
0.9829
0.0258
2.0
5808
0.0742
0.8769
0.8705
0.8737
0.9843
0.0166
3.0
8712
0.0799
0.8927
0.8649
0.8786
0.9853
Framework versions
Transformers 4.11.2
Pytorch 1.9.0+cu102
Datasets 1.12.1
Tokenizers 0.10.3
