---
base_model: finiteautomata/bertweet-base-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bertweet-olid
  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. -->

# bertweet-olid

This model is a fine-tuned version of [finiteautomata/bertweet-base-sentiment-analysis](https://huggingface.co./finiteautomata/bertweet-base-sentiment-analysis) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0303
- Accuracy: 0.8104
- F1: 0.8082

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3675        | 1.0   | 774  | 0.4257          | 0.8233   | 0.8217 |
| 0.3006        | 2.0   | 1548 | 0.3651          | 0.8385   | 0.8383 |
| 0.2461        | 3.0   | 2322 | 0.4812          | 0.8301   | 0.8298 |
| 0.202         | 4.0   | 3096 | 0.6835          | 0.8324   | 0.8324 |
| 0.1533        | 5.0   | 3870 | 1.0303          | 0.8104   | 0.8082 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2