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: []
datasets:
- vishnun/NLP-KnowledgeGraph
knowledge-graph-nlp
This model is a fine-tuned version of 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