---
base_model: distilbert-base-uncased
library_name: peft
license: apache-2.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-ner-lorafinetune-runs-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-ner-lorafinetune-runs-v1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0735
- Precision: 0.9638
- Recall: 0.9778
- F1: 0.9708
- Accuracy: 0.9888

## 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: 0.0004
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0808        | 1.0   | 2643  | 0.1186          | 0.9399    | 0.9629 | 0.9513 | 0.9818   |
| 0.0648        | 2.0   | 5286  | 0.0807          | 0.9556    | 0.9736 | 0.9645 | 0.9868   |
| 0.0366        | 3.0   | 7929  | 0.0761          | 0.9611    | 0.9770 | 0.9690 | 0.9883   |
| 0.0306        | 4.0   | 10572 | 0.0735          | 0.9638    | 0.9778 | 0.9708 | 0.9888   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1