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modernbert-base-conll2012_ontonotesv5-english_v4-ner – AI Model by fongios | AlphaNeural AI
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modernbert-base-conll2012_ontonotesv5-english_v4-ner
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transformers
safetensors
modernbert
token-classification
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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modernbert-base-conll2012_ontonotesv5-english_v4-ner
This model is a fine-tuned version of
answerdotai/ModernBERT-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0679
Precision: 0.8636
Recall: 0.8704
F1: 0.8670
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: 0.0005
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
0.0698
1.0
2350
0.0795
0.8121
0.8344
0.8231
0.0356
2.0
4700
0.0707
0.8438
0.8575
0.8506
0.0184
3.0
7050
0.0795
0.8461
0.8567
0.8513
Framework versions
Transformers 4.48.0
Pytorch 2.5.0+cu124
Datasets 3.1.0
Tokenizers 0.21.0
