---
base_model: UBC-NLP/MARBERTv2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune
  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. -->

# OTE-NoDapt-ABSA-bert-base-MARBERTv2-DefultHp-FineTune

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: 0.1711
- Precision: 0.7538
- Recall: 0.7902
- F1: 0.7716
- Accuracy: 0.9536

## 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: 32
- eval_batch_size: 8
- seed: 25
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1914        | 1.0   | 121  | 0.1169          | 0.7655    | 0.7369 | 0.7510 | 0.9536   |
| 0.0946        | 2.0   | 242  | 0.1192          | 0.7952    | 0.7334 | 0.7631 | 0.9558   |
| 0.0643        | 3.0   | 363  | 0.1336          | 0.7471    | 0.7932 | 0.7695 | 0.9537   |
| 0.0428        | 4.0   | 484  | 0.1585          | 0.7312    | 0.7957 | 0.7621 | 0.9517   |
| 0.0286        | 5.0   | 605  | 0.1711          | 0.7538    | 0.7902 | 0.7716 | 0.9536   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3