metadata
license: afl-3.0
base_model: Davlan/bert-base-multilingual-cased-ner-hrl
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: belajarner_bert_case
results: []
belajarner_bert_case
This model is a fine-tuned version of Davlan/bert-base-multilingual-cased-ner-hrl on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3367
- Precision: 0.8139
- Recall: 0.8422
- F1: 0.8278
- Accuracy: 0.9420
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2503 | 1.0 | 1567 | 0.2331 | 0.7484 | 0.8148 | 0.7802 | 0.9294 |
| 0.1645 | 2.0 | 3134 | 0.2307 | 0.7987 | 0.8158 | 0.8072 | 0.9363 |
| 0.1097 | 3.0 | 4701 | 0.2588 | 0.7764 | 0.8334 | 0.8039 | 0.9360 |
| 0.0822 | 4.0 | 6268 | 0.2624 | 0.8056 | 0.8389 | 0.8219 | 0.9409 |
| 0.061 | 5.0 | 7835 | 0.2927 | 0.8183 | 0.8275 | 0.8229 | 0.9414 |
| 0.0407 | 6.0 | 9402 | 0.3156 | 0.8021 | 0.8350 | 0.8182 | 0.9399 |
| 0.0315 | 7.0 | 10969 | 0.3257 | 0.8102 | 0.8381 | 0.8239 | 0.9413 |
| 0.0238 | 8.0 | 12536 | 0.3367 | 0.8139 | 0.8422 | 0.8278 | 0.9420 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2