metadata
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: []
Docket_Classification_NER_04_15
This model is a fine-tuned version of 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