---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: Docket_Classification_NER_04_15
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Docket_Classification_NER_04_15

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5623
- Precision: 0.8737
- Recall: 0.8823
- F1: 0.8760

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|
| No log        | 1.0    | 21   | 0.4220          | 0.8540    | 0.8819 | 0.8621 |
| No log        | 2.0    | 42   | 0.4700          | 0.8680    | 0.8596 | 0.8620 |
| No log        | 3.0    | 63   | 0.4701          | 0.8683    | 0.8705 | 0.8682 |
| No log        | 4.0    | 84   | 0.5636          | 0.8680    | 0.8765 | 0.8698 |
| No log        | 4.7901 | 100  | 0.5623          | 0.8737    | 0.8823 | 0.8760 |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1