---
base_model: jsylee/scibert_scivocab_uncased-finetuned-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: scibert-finetuned_ADEs_SonatafyAI
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# scibert-finetuned_ADEs_SonatafyAI

This model is a fine-tuned version of [jsylee/scibert_scivocab_uncased-finetuned-ner](https://huggingface.co/jsylee/scibert_scivocab_uncased-finetuned-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2004
- Precision: 0.6454
- Recall: 0.6962
- F1: 0.6698
- Accuracy: 0.9095

## 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: 5e-07
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2918        | 1.0   | 640  | 0.2240          | 0.6095    | 0.7148 | 0.6579 | 0.9029   |
| 0.2305        | 2.0   | 1280 | 0.2064          | 0.6354    | 0.6896 | 0.6614 | 0.9079   |
| 0.2223        | 3.0   | 1920 | 0.2031          | 0.636     | 0.6951 | 0.6642 | 0.9082   |
| 0.2145        | 4.0   | 2560 | 0.2010          | 0.6419    | 0.6973 | 0.6684 | 0.9089   |
| 0.2081        | 5.0   | 3200 | 0.2004          | 0.6454    | 0.6962 | 0.6698 | 0.9095   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1