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: 0.1198
- Precision: 0.8118
- Recall: 0.8560
- F1: 0.8333
- Accuracy: 0.9732
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 | 276 | 0.2493 | 0.5422 | 0.4216 | 0.4744 | 0.9417 |
| 0.3195 | 2.0 | 552 | 0.1788 | 0.7273 | 0.7019 | 0.7143 | 0.9602 |
| 0.3195 | 3.0 | 828 | 0.1485 | 0.7550 | 0.7428 | 0.7488 | 0.9633 |
| 0.1376 | 4.0 | 1104 | 0.1542 | 0.7092 | 0.7956 | 0.7499 | 0.9619 |
| 0.1376 | 5.0 | 1380 | 0.1326 | 0.7449 | 0.8135 | 0.7777 | 0.9658 |
| 0.0887 | 6.0 | 1656 | 0.1152 | 0.8228 | 0.8305 | 0.8266 | 0.9728 |
| 0.0887 | 7.0 | 1932 | 0.1223 | 0.7721 | 0.8424 | 0.8057 | 0.9692 |
| 0.0639 | 8.0 | 2208 | 0.1184 | 0.7852 | 0.8501 | 0.8164 | 0.9721 |
| 0.0639 | 9.0 | 2484 | 0.1184 | 0.8252 | 0.8484 | 0.8366 | 0.9734 |
| 0.0505 | 10.0 | 2760 | 0.1198 | 0.8118 | 0.8560 | 0.8333 | 0.9732 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1