---
language:
- en
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ade-v2-classification
  results: []
---

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# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-ade-v2-classification

This model is a fine-tuned version of [BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the ade_corpus_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1982
- Accuracy: 0.9611

## 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: 1.8069489920382708e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1657        | 1.0   | 1176 | 0.1405          | 0.9511   |
| 0.1019        | 2.0   | 2352 | 0.1767          | 0.9575   |
| 0.055         | 3.0   | 3528 | 0.1982          | 0.9611   |
| 0.0424        | 4.0   | 4704 | 0.2038          | 0.9605   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2