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

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

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: 0.2103
- Precision: 0.6454
- Recall: 0.6510
- F1: 0.6482
- Accuracy: 0.9098

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2952        | 1.0   | 640  | 0.2368          | 0.5806    | 0.6360 | 0.6071 | 0.8992   |
| 0.2315        | 2.0   | 1280 | 0.2196          | 0.6321    | 0.6403 | 0.6362 | 0.9047   |
| 0.2197        | 3.0   | 1920 | 0.2143          | 0.6340    | 0.6510 | 0.6424 | 0.9061   |
| 0.2105        | 4.0   | 2560 | 0.2112          | 0.6467    | 0.6488 | 0.6478 | 0.9092   |
| 0.2078        | 5.0   | 3200 | 0.2103          | 0.6454    | 0.6510 | 0.6482 | 0.9098   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1