--- license: apache-2.0 base_model: google-bert/bert-base-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: BERT-full-finetuned-ner-pablo results: [] --- # BERT-full-finetuned-ner-pablo This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1071 - Precision: 0.7993 - Recall: 0.7887 - F1: 0.7940 - Accuracy: 0.9768 ## 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: 0.0002 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.05 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 0.9923 | 97 | 0.1037 | 0.7655 | 0.7399 | 0.7525 | 0.9725 | | No log | 1.9949 | 195 | 0.0907 | 0.8123 | 0.7488 | 0.7792 | 0.9759 | | No log | 2.9974 | 293 | 0.0922 | 0.7739 | 0.7872 | 0.7805 | 0.9758 | | No log | 4.0 | 391 | 0.0986 | 0.7856 | 0.7895 | 0.7875 | 0.9760 | | No log | 4.9616 | 485 | 0.1071 | 0.7993 | 0.7887 | 0.7940 | 0.9768 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1