---
base_model: qarib/bert-base-qarib
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: OTE-NoDapt-ABSA-bert-base-qarib-OrginalHP-FineTune
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# OTE-NoDapt-ABSA-bert-base-qarib-OrginalHP-FineTune

This model is a fine-tuned version of [qarib/bert-base-qarib](https://huggingface.co/qarib/bert-base-qarib) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1348
- Precision: 0.7488
- Recall: 0.7723
- F1: 0.7604
- Accuracy: 0.9532

## 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: 8e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1656        | 1.0   | 61   | 0.1196          | 0.7299    | 0.7932 | 0.7603 | 0.9528   |
| 0.08          | 2.0   | 122  | 0.1176          | 0.7561    | 0.7678 | 0.7619 | 0.9543   |
| 0.0501        | 3.0   | 183  | 0.1348          | 0.7488    | 0.7723 | 0.7604 | 0.9532   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3