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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: knowledge-graph-nlp
results: []
datasets:
- vishnun/NLP-KnowledgeGraph
language:
- en
library_name: transformers
pipeline_tag: token-classification
---
<!-- 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 [vishnun/NLP-KnowledgeGraph](https://huggingface.co/datasets/vishnun/NLP-KnowledgeGraph) 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 |