metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner
results: []
distilbert-base-uncased-finetuned-ner
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0597
- Precision: 0.9261
- Recall: 0.9357
- F1: 0.9309
- Accuracy: 0.9838
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 |
|---|---|---|---|---|---|---|---|
| 0.2408 | 1.0 | 878 | 0.0700 | 0.9123 | 0.9228 | 0.9175 | 0.9805 |
| 0.0501 | 2.0 | 1756 | 0.0602 | 0.9189 | 0.9305 | 0.9247 | 0.9828 |
| 0.0304 | 3.0 | 2634 | 0.0597 | 0.9261 | 0.9357 | 0.9309 | 0.9838 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Tokenizers 0.12.1