---
library_name: transformers
license: apache-2.0
base_model: dslim/distilbert-NER
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-NER-finetuned-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-NER-finetuned-ner

This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0111
- Precision: 0.8892
- Recall: 0.9189
- F1: 0.9038
- Accuracy: 0.9968

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 270  | 0.0155          | 0.8292    | 0.8918 | 0.8594 | 0.9952   |
| 0.0286        | 2.0   | 540  | 0.0121          | 0.8695    | 0.9198 | 0.8939 | 0.9965   |
| 0.0286        | 3.0   | 810  | 0.0111          | 0.8892    | 0.9189 | 0.9038 | 0.9968   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1