---
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-custom-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-custom-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: 0.7017
- Precision: 0.2292
- Recall: 0.275
- F1: 0.25
- Accuracy: 0.8598

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 1    | 0.8583          | 0.1045    | 0.175  | 0.1308 | 0.8084   |
| No log        | 2.0   | 2    | 0.7963          | 0.1228    | 0.175  | 0.1443 | 0.8271   |
| No log        | 3.0   | 3    | 0.7497          | 0.1837    | 0.225  | 0.2022 | 0.8505   |
| No log        | 4.0   | 4    | 0.7179          | 0.1837    | 0.225  | 0.2022 | 0.8505   |
| No log        | 5.0   | 5    | 0.7017          | 0.2292    | 0.275  | 0.25   | 0.8598   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.14.1
- Tokenizers 0.19.1