metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: kg_model
results: []
kg_model
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: 0.3039
- 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