metadata

library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
model-index:
  - name: modernbert-base-conll2012_ontonotesv5-english_v4-ner
    results: []

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: 0.0756
Precision: 0.8463
Recall: 0.8628
F1: 0.8545

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
0.0683	1.0	2350	0.0765	0.8224	0.8438	0.8329
0.0353	2.0	4700	0.0692	0.8427	0.8651	0.8537
0.0189	3.0	7050	0.0756	0.8463	0.8628	0.8545

Framework versions

Transformers 4.48.0.dev0
Pytorch 2.5.0+cu124
Datasets 3.1.0
Tokenizers 0.21.0