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---
tags:
- generated_from_trainer
datasets:
- jnlpba
metrics:
- precision
- recall
- f1
- accuracy
widget:
- text: The widespread circular form of DNA molecules inside cells creates very serious
topological problems during replication. Due to the helical structure of the double
helix the parental strands of circular DNA form a link of very high order, and
yet they have to be unlinked before the cell division.
- text: It consists of 25 exons encoding a 1,278-amino acid glycoprotein that is composed
of 13 transmembrane domains
base_model: allenai/scibert_scivocab_uncased
model-index:
- name: scibert-finetuned-ner
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: jnlpba
type: jnlpba
config: jnlpba
split: train
args: jnlpba
metrics:
- type: precision
value: 0.6737190414118119
name: Precision
- type: recall
value: 0.7756869083352574
name: Recall
- type: f1
value: 0.7211161792326267
name: F1
- type: accuracy
value: 0.9226268866380928
name: Accuracy
---
<!-- 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_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the jnlpba dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4717
- Precision: 0.6737
- Recall: 0.7757
- F1: 0.7211
- Accuracy: 0.9226
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1608 | 1.0 | 2319 | 0.2431 | 0.6641 | 0.7581 | 0.7080 | 0.9250 |
| 0.103 | 2.0 | 4638 | 0.2916 | 0.6739 | 0.7803 | 0.7232 | 0.9228 |
| 0.0659 | 3.0 | 6957 | 0.3662 | 0.6796 | 0.7624 | 0.7186 | 0.9233 |
| 0.0393 | 4.0 | 9276 | 0.4222 | 0.6737 | 0.7771 | 0.7217 | 0.9225 |
| 0.025 | 5.0 | 11595 | 0.4717 | 0.6737 | 0.7757 | 0.7211 | 0.9226 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|