---
base_model: UBC-NLP/MARBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: marbert-finetuned-wanlp_sarcasm
  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-finetuned-wanlp_sarcasm

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: 0.6362
- Accuracy: 0.9485
- Precision: 0.7758
- Recall: 0.7814
- F1: 0.7786

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2904        | 1.0   | 226  | 0.4947          | 0.9402   | 0.8199    | 0.6201 | 0.7061 |
| 0.2199        | 2.0   | 452  | 0.4060          | 0.9406   | 0.7345    | 0.7634 | 0.7487 |
| 0.0545        | 3.0   | 678  | 0.6362          | 0.9485   | 0.7758    | 0.7814 | 0.7786 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1