---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: kg_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# kg_model

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: 0.3039
- Precision: 0.7629
- Recall: 0.7025
- F1: 0.7315
- Accuracy: 0.8965

## Model description

Lite model to extract entities and relation between them, could be leveraged for Question Answering and Querying tasks.

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3736        | 1.0   | 1063 | 0.3379          | 0.7542    | 0.6217 | 0.6816 | 0.8813   |
| 0.3078        | 2.0   | 2126 | 0.3075          | 0.7728    | 0.6678 | 0.7164 | 0.8929   |
| 0.267         | 3.0   | 3189 | 0.3017          | 0.7597    | 0.6999 | 0.7285 | 0.8954   |
| 0.2455        | 4.0   | 4252 | 0.3039          | 0.7629    | 0.7025 | 0.7315 | 0.8965   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2