| | --- |
| | base_model: allenai/scibert_scivocab_uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: scibert-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-ner |
| |
|
| | This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1809 |
| | - Precision: 0.4499 |
| | - Recall: 0.4637 |
| | - F1: 0.4567 |
| | - Accuracy: 0.9536 |
| |
|
| | ## 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: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 60 | 0.1967 | 0.3563 | 0.3184 | 0.3363 | 0.9509 | |
| | | No log | 2.0 | 120 | 0.1726 | 0.4077 | 0.3855 | 0.3963 | 0.9525 | |
| | | No log | 3.0 | 180 | 0.1723 | 0.4204 | 0.4721 | 0.4447 | 0.9529 | |
| | | No log | 4.0 | 240 | 0.1775 | 0.4248 | 0.4735 | 0.4478 | 0.9526 | |
| | | No log | 5.0 | 300 | 0.1809 | 0.4499 | 0.4637 | 0.4567 | 0.9536 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.34.1 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| |
|
