---
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: 0.2719
- Precision: 0.8636
- Recall: 0.8409
- F1: 0.8521
- Accuracy: 0.9291

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1915        | 1.0   | 855  | 0.2499          | 0.8465    | 0.8228 | 0.8345 | 0.9227   |
| 0.1345        | 2.0   | 1710 | 0.2609          | 0.8528    | 0.8370 | 0.8448 | 0.9259   |
| 0.1078        | 3.0   | 2565 | 0.2664          | 0.8558    | 0.8450 | 0.8504 | 0.9285   |
| 0.0949        | 4.0   | 3420 | 0.2719          | 0.8636    | 0.8409 | 0.8521 | 0.9291   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1