README.md

---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-ner-finer
  results: []
datasets:
- nlpaueb/finer-139
language:
- en
metrics:
- accuracy
- precision
- f1
- confusion_matrix
base_model:
- distilbert/distilbert-base-uncased
---

<!-- 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. -->

# distilbert-base-uncased-ner-finer

## Model description

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the [Finer-139](https://huggingface.co/datasets/nlpaueb/finer-139) dataset.

It achieves the following results on the evaluation set:
- Loss: 0.0293
- Precision: 0.8768
- Recall: 0.9064
- F1: 0.8914
- Accuracy: 0.9901

## Training and evaluation data

The training data consists of the top 4 ner_tags having the most occurence from the Finer-139 dataset plus the outside tag "O".

## Training results

| Epoch | Training Loss | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|
| 1 | 0.035700 | 0.035880 | 0.847873 | 0.890125 | 0.868486 | 0.987242 |
| 2 | 0.023700 | 0.029618 | 0.867055 | 0.906431 | 0.886306 | 0.989505 |
| 3 | 0.017000 | 0.029322 | 0.876898 | 0.906431 | 0.891420 | 0.990180 |

## Valiadtion results

| ner_tag | precision | recall | f1-score | support |
|--------------|-----------|--------|----------|---------|
| O                                            | 1.00      | 0.99      | 1.00     | 229573  |
| I-DebtInstrumentInterestRateStatedPercentage | 0.94      | 0.94      | 0.94     | 5412   |
| I-LineOfCreditFacilityMaximumBorrowingCapacity | 0.82      | 0.88      | 0.85     | 4288   |
| I-DebtInstrumentBasisSpreadOnVariableRate1    | 0.89      | 0.97      | 0.93     | 4788   |
| I-DebtInstrumentFaceAmount                    | 0.79      | 0.76      | 0.78     | 3398   |

![confusion matrix](https://cdn-uploads.huggingface.co/production/uploads/6791ddd9f0ecdeb1a8aa6883/3CftA28uzQAU6Oqi_Iddl.png)

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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
- num_epochs: 3

### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0