---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model3_Marabertv2_T1_WOS
  results: []
---

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# Model3_Marabertv2_T1_WOS

This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2308
- F1: 0.8430
- F1 Macro: 0.7804
- Roc Auc: 0.9048
- Accuracy: 0.8142

## 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-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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F1 Macro | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-------:|:--------:|
| 0.2194        | 1.0   | 507  | 0.1556          | 0.8330 | 0.7507   | 0.8909  | 0.7947   |
| 0.1166        | 2.0   | 1014 | 0.1850          | 0.8269 | 0.7439   | 0.8920  | 0.8010   |
| 0.0747        | 3.0   | 1521 | 0.1915          | 0.8368 | 0.7724   | 0.8992  | 0.8115   |
| 0.0445        | 4.0   | 2028 | 0.2034          | 0.8398 | 0.7695   | 0.9014  | 0.8149   |
| 0.0301        | 5.0   | 2535 | 0.2308          | 0.8430 | 0.7804   | 0.9048  | 0.8142   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3