---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Sentiment-Analysis-Model
  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. -->

# Sentiment-Analysis-Model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7000
- Accuracy: 0.7165

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8648        | 0.5   | 500  | 0.9848          | 0.703    |
| 0.8367        | 1.0   | 1000 | 0.8764          | 0.683    |
| 0.7815        | 1.5   | 1500 | 0.7792          | 0.7145   |
| 0.7751        | 2.0   | 2000 | 0.7516          | 0.7095   |
| 0.8081        | 2.5   | 2500 | 0.7783          | 0.7055   |
| 0.8142        | 3.0   | 3000 | 0.8125          | 0.688    |
| 0.8497        | 3.5   | 3500 | 0.8383          | 0.6575   |
| 0.8006        | 4.0   | 4000 | 0.7412          | 0.705    |
| 0.7363        | 4.5   | 4500 | 0.7299          | 0.718    |
| 0.7151        | 5.0   | 5000 | 0.7000          | 0.7165   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3