---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-fin_ner
  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. -->

# distilbert-base-uncased-finetuned-fin_ner

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0887
- Precision: 0.8198
- Recall: 0.8292
- F1: 0.8245
- Accuracy: 0.9804

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 204  | 0.0877          | 0.6569    | 0.7734 | 0.7104 | 0.9709   |
| No log        | 2.0   | 408  | 0.0683          | 0.7931    | 0.7931 | 0.7931 | 0.9784   |
| 0.1032        | 3.0   | 612  | 0.0657          | 0.8325    | 0.8079 | 0.82   | 0.9796   |
| 0.1032        | 4.0   | 816  | 0.0696          | 0.7942    | 0.8112 | 0.8026 | 0.9783   |
| 0.0148        | 5.0   | 1020 | 0.0742          | 0.7987    | 0.8276 | 0.8129 | 0.9796   |
| 0.0148        | 6.0   | 1224 | 0.0788          | 0.7870    | 0.8374 | 0.8115 | 0.9787   |
| 0.0148        | 7.0   | 1428 | 0.0833          | 0.7933    | 0.8128 | 0.8029 | 0.9792   |
| 0.0066        | 8.0   | 1632 | 0.0833          | 0.8237    | 0.8440 | 0.8337 | 0.9806   |
| 0.0066        | 9.0   | 1836 | 0.0860          | 0.8185    | 0.8292 | 0.8238 | 0.9805   |
| 0.0042        | 10.0  | 2040 | 0.0887          | 0.8198    | 0.8292 | 0.8245 | 0.9804   |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2