---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fine-tuned-marBERT_latest
  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. -->

# fine-tuned-marBERT_latest

This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1243
- Accuracy: 0.9712
- Precision: 0.9730
- Recall: 0.9836
- F1: 0.9783

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1558        | 1.0   | 56232  | 0.1159          | 0.9693   | 0.9734    | 0.9802 | 0.9768 |
| 0.1245        | 2.0   | 112464 | 0.1427          | 0.9696   | 0.9724    | 0.9817 | 0.9770 |
| 0.1061        | 3.0   | 168696 | 0.1262          | 0.9716   | 0.9760    | 0.9810 | 0.9785 |
| 0.0925        | 4.0   | 224928 | 0.1243          | 0.9712   | 0.9730    | 0.9836 | 0.9783 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1