metadata
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: []
knowledge-graph-nlp
This model is a fine-tuned version of distilbert-base-uncased on the vishnun/NLP-KnowledgeGraph dataset. It achieves the following results on the evaluation set:
- Loss: 0.1765
- Precision: 0.9013
- Recall: 0.8807
- F1: 0.8909
- Accuracy: 0.9487
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 |
|---|---|---|---|---|---|---|---|
| 0.2841 | 1.0 | 2316 | 0.2421 | 0.8382 | 0.8124 | 0.8251 | 0.9189 |
| 0.1925 | 2.0 | 4632 | 0.1946 | 0.8752 | 0.8567 | 0.8658 | 0.9373 |
| 0.1539 | 3.0 | 6948 | 0.1815 | 0.8912 | 0.8735 | 0.8822 | 0.9449 |
| 0.1285 | 4.0 | 9264 | 0.1765 | 0.9013 | 0.8807 | 0.8909 | 0.9487 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2