---
library_name: transformers
base_model: UBC-NLP/MARBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MARBERT
  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. -->

# MARBERT

This model is a fine-tuned version of [UBC-NLP/MARBERT](https://huggingface.co/UBC-NLP/MARBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0270
- Precision: 0.4848
- Recall: 0.6957
- F1: 0.5714
- Accuracy: 0.6772

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 5    | 0.8519          | 0.0       | 0.0    | 0.0    | 0.625    |
| No log        | 2.0   | 10   | 0.8108          | 0.0       | 0.0    | 0.0    | 0.6806   |
| No log        | 3.0   | 15   | 0.7524          | 0.0       | 0.0    | 0.0    | 0.7361   |
| No log        | 4.0   | 20   | 0.6927          | 0.2222    | 0.2857 | 0.25   | 0.7083   |
| No log        | 5.0   | 25   | 0.6995          | 0.0       | 0.0    | 0.0    | 0.7222   |
| No log        | 6.0   | 30   | 0.8241          | 0.1818    | 0.2857 | 0.2222 | 0.625    |
| No log        | 7.0   | 35   | 0.6811          | 0.2222    | 0.2857 | 0.25   | 0.75     |
| No log        | 8.0   | 40   | 0.6957          | 0.25      | 0.2857 | 0.2667 | 0.7639   |
| No log        | 9.0   | 45   | 0.7392          | 0.2222    | 0.2857 | 0.25   | 0.6944   |
| No log        | 10.0  | 50   | 0.7612          | 0.2222    | 0.2857 | 0.25   | 0.6944   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0