metadata
license: apache-2.0
base_model: distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-NER
results: []
distilbert-NER
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0710
- Precision: 0.9202
- Recall: 0.9232
- F1: 0.9217
- Accuracy: 0.9810
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2748 | 1.0 | 878 | 0.0959 | 0.8886 | 0.8976 | 0.8931 | 0.9739 |
| 0.0635 | 2.0 | 1756 | 0.0721 | 0.9199 | 0.9228 | 0.9213 | 0.9805 |
| 0.0411 | 3.0 | 2634 | 0.0710 | 0.9202 | 0.9232 | 0.9217 | 0.9810 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1