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---
tags:
- generated_from_trainer
datasets:
- ncbi_disease
metrics:
- precision
- recall
- f1
- accuracy
model_index:
- name: biobert_v1.1_pubmed-finetuned-ner-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ncbi_disease
type: ncbi_disease
args: ncbi_disease
metric:
name: Accuracy
type: accuracy
value: 0.9829142288061745
---
<!-- 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. -->
# biobert_v1.1_pubmed-finetuned-ner-finetuned-ner
This model is a fine-tuned version of [fidukm34/biobert_v1.1_pubmed-finetuned-ner](https://huggingface.co/fidukm34/biobert_v1.1_pubmed-finetuned-ner) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0715
- Precision: 0.8464
- Recall: 0.8872
- F1: 0.8663
- Accuracy: 0.9829
## 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 340 | 0.0715 | 0.8464 | 0.8872 | 0.8663 | 0.9829 |
### Framework versions
- Transformers 4.8.1
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
|