--- base_model: allenai/scibert_scivocab_cased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: scibert-finetuned-ner 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. --> # scibert-finetuned-ner This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3459 - Precision: 0.5666 - Recall: 0.5191 - F1: 0.5418 - Accuracy: 0.9363 ## 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 121 | 0.3648 | 0.3157 | 0.3390 | 0.3269 | 0.8945 | | No log | 2.0 | 242 | 0.3177 | 0.5280 | 0.3348 | 0.4097 | 0.9253 | | No log | 3.0 | 363 | 0.2599 | 0.5143 | 0.4326 | 0.4700 | 0.9315 | | No log | 4.0 | 484 | 0.2825 | 0.5360 | 0.4227 | 0.4726 | 0.9336 | | 0.2574 | 5.0 | 605 | 0.2968 | 0.5473 | 0.4922 | 0.5183 | 0.9350 | | 0.2574 | 6.0 | 726 | 0.3193 | 0.5857 | 0.4894 | 0.5332 | 0.9377 | | 0.2574 | 7.0 | 847 | 0.3327 | 0.5513 | 0.4879 | 0.5177 | 0.9356 | | 0.2574 | 8.0 | 968 | 0.3315 | 0.5658 | 0.5121 | 0.5376 | 0.9363 | | 0.0678 | 9.0 | 1089 | 0.3413 | 0.5465 | 0.5163 | 0.5310 | 0.9361 | | 0.0678 | 10.0 | 1210 | 0.3459 | 0.5666 | 0.5191 | 0.5418 | 0.9363 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1