---
base_model: gyesibiney/covid-tweet-sentimental-Analysis-roberta
tags:
- generated_from_trainer
model-index:
- name: test_trainer
  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. -->

# test_trainer

This model is a fine-tuned version of [gyesibiney/covid-tweet-sentimental-Analysis-roberta](https://huggingface.co/gyesibiney/covid-tweet-sentimental-Analysis-roberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5256

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6341        | 0.2   | 500  | 0.6156          |
| 0.5846        | 0.4   | 1000 | 0.6548          |
| 0.5447        | 0.6   | 1500 | 0.5651          |
| 0.523         | 0.8   | 2000 | 0.4769          |
| 0.5087        | 1.0   | 2500 | 0.4937          |
| 0.4791        | 1.2   | 3000 | 0.4567          |
| 0.4681        | 1.41  | 3500 | 0.4609          |
| 0.4255        | 1.61  | 4000 | 0.5214          |
| 0.4474        | 1.81  | 4500 | 0.5182          |
| 0.4271        | 2.01  | 5000 | 0.4983          |
| 0.4008        | 2.21  | 5500 | 0.4944          |
| 0.384         | 2.41  | 6000 | 0.4585          |
| 0.3629        | 2.61  | 6500 | 0.5462          |
| 0.3695        | 2.81  | 7000 | 0.5256          |


### Framework versions

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