---
base_model: KISTI-AI/scideberta-cs
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: scideberta-cs-ner
  results: []
---

<!-- 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. -->

# scideberta-cs-ner

This model is a fine-tuned version of [KISTI-AI/scideberta-cs](https://huggingface.co/KISTI-AI/scideberta-cs) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1552
- Precision: 0.4943
- Recall: 0.5475
- F1: 0.5195
- Accuracy: 0.9589

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 60   | 0.1980          | 0.3445    | 0.2723 | 0.3042 | 0.9530   |
| No log        | 2.0   | 120  | 0.1579          | 0.4444    | 0.4358 | 0.4401 | 0.9582   |
| No log        | 3.0   | 180  | 0.1520          | 0.4751    | 0.5321 | 0.5020 | 0.9568   |
| No log        | 4.0   | 240  | 0.1518          | 0.4955    | 0.5433 | 0.5183 | 0.9592   |
| No log        | 5.0   | 300  | 0.1552          | 0.4943    | 0.5475 | 0.5195 | 0.9589   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1