---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: knowledge-graph-nlp
  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. -->

# knowledge-graph-nlp

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: 0.1830
- Precision: 0.8988
- Recall: 0.8715
- F1: 0.8849
- Accuracy: 0.9453

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2908        | 1.0   | 2316 | 0.2461          | 0.8455    | 0.8023 | 0.8234 | 0.9167   |
| 0.1973        | 2.0   | 4632 | 0.2000          | 0.8745    | 0.8446 | 0.8593 | 0.9341   |
| 0.1593        | 3.0   | 6948 | 0.1863          | 0.8973    | 0.8632 | 0.8799 | 0.9427   |
| 0.1336        | 4.0   | 9264 | 0.1830          | 0.8988    | 0.8715 | 0.8849 | 0.9453   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2