metadata
base_model: konverner/distilcamembert-base-ner-address
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Method-1-model-2
results: []
Method-1-model-2
This model is a fine-tuned version of konverner/distilcamembert-base-ner-address on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1194
- Precision: 0.9268
- Recall: 1.0
- F1: 0.9620
- Accuracy: 0.9848
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 64 | 0.1575 | 0.7778 | 0.9211 | 0.8434 | 0.9727 |
| No log | 2.0 | 128 | 0.1508 | 0.95 | 1.0 | 0.9744 | 0.9783 |
| No log | 3.0 | 192 | 0.1194 | 0.9268 | 1.0 | 0.9620 | 0.9848 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1