metadata
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilroberta-base-finetuned-ner-harem
results: []
distilroberta-base-finetuned-ner-harem
This model is a fine-tuned version of distilbert/distilroberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2169
- Precision: 0.6576
- Recall: 0.6851
- F1: 0.6711
- Accuracy: 0.9489
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 282 | 0.2950 | 0.4796 | 0.4388 | 0.4583 | 0.9183 |
| 0.3687 | 2.0 | 564 | 0.2216 | 0.5693 | 0.5821 | 0.5756 | 0.9362 |
| 0.3687 | 3.0 | 846 | 0.2170 | 0.5850 | 0.6060 | 0.5953 | 0.9373 |
| 0.1701 | 4.0 | 1128 | 0.1990 | 0.6352 | 0.6522 | 0.6436 | 0.9464 |
| 0.1701 | 5.0 | 1410 | 0.1978 | 0.6558 | 0.6910 | 0.6730 | 0.9481 |
| 0.1123 | 6.0 | 1692 | 0.1998 | 0.6378 | 0.6701 | 0.6536 | 0.9495 |
| 0.1123 | 7.0 | 1974 | 0.2112 | 0.6643 | 0.6851 | 0.6745 | 0.9490 |
| 0.0809 | 8.0 | 2256 | 0.2153 | 0.6571 | 0.6806 | 0.6686 | 0.9480 |
| 0.0572 | 9.0 | 2538 | 0.2133 | 0.6647 | 0.6836 | 0.6740 | 0.9502 |
| 0.0572 | 10.0 | 2820 | 0.2169 | 0.6576 | 0.6851 | 0.6711 | 0.9489 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1