---
base_model: dmis-lab/biobert-base-cased-v1.1
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: cer_model-iii
  results: []
---

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

This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2146
- Precision: 0.9186
- Recall: 0.8689
- F1: 0.8931
- Accuracy: 0.9355

## 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: 0.0002
- 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
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0124        | 1.0   | 4841  | 0.2169          | 0.9157    | 0.8545 | 0.8841 | 0.9272   |
| 0.0025        | 2.0   | 9682  | 0.2221          | 0.9180    | 0.8708 | 0.8938 | 0.9318   |
| 0.0001        | 3.0   | 14523 | 0.2146          | 0.9186    | 0.8689 | 0.8931 | 0.9355   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1