---
library_name: transformers
base_model: finiteautomata/bertweet-base-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bertweet-sentiment-finetuned
  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-sentiment-finetuned

This model is a fine-tuned version of [finiteautomata/bertweet-base-sentiment-analysis](https://huggingface.co/finiteautomata/bertweet-base-sentiment-analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5533
- Accuracy: 0.875
- F1: 0.8633

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 60   | 0.4306          | 0.85     | 0.8349 |
| No log        | 2.0   | 120  | 0.3752          | 0.8917   | 0.8844 |
| No log        | 3.0   | 180  | 0.5461          | 0.8417   | 0.8230 |
| No log        | 4.0   | 240  | 0.5316          | 0.875    | 0.8633 |
| No log        | 5.0   | 300  | 0.5533          | 0.875    | 0.8633 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.4.1+cpu
- Datasets 3.1.0
- Tokenizers 0.21.0