---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Arsarcasm
  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. -->

# Arsarcasm

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: 0.3985
- Accuracy: 0.8757
- F1 Weighted: 0.8778
- Roc Auc: 0.7900

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-------:|
| 0.3098        | 1.0   | 1050 | 0.3747          | 0.8634   | 0.8383      | 0.6305  |
| 0.2456        | 2.0   | 2100 | 0.3985          | 0.8757   | 0.8778      | 0.7900  |
| 0.1446        | 3.0   | 3150 | 0.5968          | 0.8786   | 0.8711      | 0.7262  |
| 0.0932        | 4.0   | 4200 | 0.6484          | 0.8738   | 0.8737      | 0.7678  |
| 0.0556        | 5.0   | 5250 | 0.7629          | 0.8767   | 0.8745      | 0.7578  |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2