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---
tags:
- generated_from_trainer
datasets:
- ncbi_disease
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electramed-small-NCBI-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: ncbi_disease
type: ncbi_disease
config: ncbi_disease
split: train
args: ncbi_disease
metrics:
- name: Precision
type: precision
value: 0.8083491461100569
- name: Recall
type: recall
value: 0.8875
- name: F1
type: f1
value: 0.846077457795432
- name: Accuracy
type: accuracy
value: 0.9820794382985671
---
<!-- 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. -->
# electramed-small-NCBI-ner
This model is a fine-tuned version of [giacomomiolo/electramed_small_scivocab](https://huggingface.co/giacomomiolo/electramed_small_scivocab) on the ncbi_disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0664
- Precision: 0.8083
- Recall: 0.8875
- F1: 0.8461
- Accuracy: 0.9821
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4787 | 1.0 | 340 | 0.5090 | 0.6090 | 0.5062 | 0.5529 | 0.9608 |
| 0.2029 | 2.0 | 680 | 0.1890 | 0.7643 | 0.8208 | 0.7916 | 0.9774 |
| 0.1402 | 3.0 | 1020 | 0.1106 | 0.7839 | 0.8802 | 0.8292 | 0.9807 |
| 0.075 | 4.0 | 1360 | 0.0876 | 0.8162 | 0.8698 | 0.8422 | 0.9817 |
| 0.0408 | 5.0 | 1700 | 0.0776 | 0.8090 | 0.8781 | 0.8422 | 0.9818 |
| 0.0308 | 6.0 | 2040 | 0.0697 | 0.8044 | 0.8823 | 0.8415 | 0.9825 |
| 0.0405 | 7.0 | 2380 | 0.0680 | 0.8118 | 0.8854 | 0.8470 | 0.9830 |
| 0.0138 | 8.0 | 2720 | 0.0665 | 0.8111 | 0.8854 | 0.8466 | 0.9826 |
| 0.0223 | 9.0 | 3060 | 0.0675 | 0.8064 | 0.8896 | 0.8460 | 0.9821 |
| 0.0395 | 10.0 | 3400 | 0.0664 | 0.8083 | 0.8875 | 0.8461 | 0.9821 |
### Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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