---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# modernbert-base-conll2012_ontonotesv5-english_v4-ner

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/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