--- license: apache-2.0 base_model: surrey-nlp/albert-large-v2-finetuned-abbDet tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: albert-large-v2-finetuned-abbDet-finetuned-ner-Custom 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. --> # albert-large-v2-finetuned-abbDet-finetuned-ner-Custom This model is a fine-tuned version of [surrey-nlp/albert-large-v2-finetuned-abbDet](https://huggingface.co/surrey-nlp/albert-large-v2-finetuned-abbDet) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1315 - Precision: 0.9768 - Recall: 0.9733 - F1: 0.9750 - Accuracy: 0.9731 ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.15.1