--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: anercorpDataset_v2.1 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # anercorpDataset_v2.1 This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-mix-ner](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-ner) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2755 - Precision: 0.7604 - Recall: 0.6878 - F1: 0.7223 - Accuracy: 0.9461 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.206 | 1.0 | 7057 | 0.2703 | 0.6971 | 0.6367 | 0.6655 | 0.9377 | | 0.2036 | 2.0 | 14114 | 0.2438 | 0.7460 | 0.6756 | 0.7090 | 0.9449 | | 0.1404 | 3.0 | 21171 | 0.2755 | 0.7604 | 0.6878 | 0.7223 | 0.9461 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3