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---
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
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