---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner-combined-v1
  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-ner-combined-v1

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2614
- Precision: 0.7181
- Recall: 0.7404
- F1: 0.7291
- Accuracy: 0.9201

## 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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 240  | 0.3337          | 0.6076    | 0.6251 | 0.6162 | 0.8959   |
| No log        | 2.0   | 480  | 0.2803          | 0.6819    | 0.6935 | 0.6876 | 0.9116   |
| 0.3943        | 3.0   | 720  | 0.2579          | 0.7206    | 0.7040 | 0.7122 | 0.9172   |
| 0.3943        | 4.0   | 960  | 0.2523          | 0.7225    | 0.7149 | 0.7187 | 0.9174   |
| 0.2108        | 5.0   | 1200 | 0.2556          | 0.7153    | 0.7288 | 0.7220 | 0.9191   |
| 0.2108        | 6.0   | 1440 | 0.2532          | 0.7234    | 0.7232 | 0.7233 | 0.9198   |
| 0.1727        | 7.0   | 1680 | 0.2614          | 0.7181    | 0.7404 | 0.7291 | 0.9201   |
| 0.1727        | 8.0   | 1920 | 0.2688          | 0.7013    | 0.7414 | 0.7208 | 0.9176   |
| 0.1407        | 9.0   | 2160 | 0.2759          | 0.7061    | 0.7449 | 0.7250 | 0.9187   |
| 0.1407        | 10.0  | 2400 | 0.2824          | 0.7161    | 0.7320 | 0.7239 | 0.9189   |
| 0.1157        | 11.0  | 2640 | 0.2891          | 0.7295    | 0.7179 | 0.7237 | 0.9200   |
| 0.1157        | 12.0  | 2880 | 0.3048          | 0.7210    | 0.7227 | 0.7218 | 0.9190   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 3.6.0
- Tokenizers 0.22.1