metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner-harem
results: []
distilbert-base-uncased-finetuned-ner-harem
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2626
- Precision: 0.5556
- Recall: 0.5565
- F1: 0.5560
- Accuracy: 0.9336
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 | 282 | 0.3748 | 0.4065 | 0.2749 | 0.3280 | 0.9053 |
| 0.403 | 2.0 | 564 | 0.2924 | 0.5558 | 0.4705 | 0.5096 | 0.9266 |
| 0.403 | 3.0 | 846 | 0.2863 | 0.6589 | 0.5278 | 0.5861 | 0.9347 |
| 0.1961 | 4.0 | 1128 | 0.2626 | 0.5556 | 0.5565 | 0.5560 | 0.9336 |
| 0.1961 | 5.0 | 1410 | 0.2710 | 0.6279 | 0.5919 | 0.6094 | 0.9403 |
| 0.1074 | 6.0 | 1692 | 0.3046 | 0.6699 | 0.5818 | 0.6227 | 0.9408 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1