metadata
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-finetuned-ner-geocorpus
results: []
distilbert-base-multilingual-cased-finetuned-ner-geocorpus
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1028
- Precision: 0.8079
- Recall: 0.8868
- F1: 0.8455
- Accuracy: 0.9747
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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 276 | 0.1866 | 0.7323 | 0.6760 | 0.7030 | 0.9551 |
| 0.2877 | 2.0 | 552 | 0.1247 | 0.7870 | 0.7788 | 0.7829 | 0.9685 |
| 0.2877 | 3.0 | 828 | 0.1125 | 0.8547 | 0.7819 | 0.8167 | 0.9719 |
| 0.0858 | 4.0 | 1104 | 0.1043 | 0.8274 | 0.8463 | 0.8368 | 0.9739 |
| 0.0858 | 5.0 | 1380 | 0.1062 | 0.8349 | 0.8349 | 0.8349 | 0.9730 |
| 0.0424 | 6.0 | 1656 | 0.1028 | 0.8079 | 0.8868 | 0.8455 | 0.9747 |
| 0.0424 | 7.0 | 1932 | 0.1139 | 0.8586 | 0.8702 | 0.8644 | 0.9769 |
| 0.0225 | 8.0 | 2208 | 0.1229 | 0.8511 | 0.9024 | 0.8760 | 0.9765 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1