---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: Model3_Marabertv2_T1_WS_A100
  results: []
---

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# Model3_Marabertv2_T1_WS_A100

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: 0.2316
- F1: 0.8336
- F1 Macro: 0.7718
- Roc Auc: 0.8974
- Accuracy: 0.8066

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-------:|:--------:|
| 0.2253        | 1.0   | 507  | 0.1618          | 0.8162 | 0.7404   | 0.8787  | 0.7814   |
| 0.1159        | 2.0   | 1014 | 0.1652          | 0.8273 | 0.7545   | 0.8928  | 0.8017   |
| 0.073         | 3.0   | 1521 | 0.1883          | 0.8355 | 0.7645   | 0.8996  | 0.8045   |
| 0.0454        | 4.0   | 2028 | 0.2138          | 0.8408 | 0.7700   | 0.9026  | 0.8128   |
| 0.0301        | 5.0   | 2535 | 0.2316          | 0.8336 | 0.7718   | 0.8974  | 0.8066   |


### Framework versions

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