---
base_model: Sonny4Sonnix/twitter-roberta-base-sentimental-analysis-of-covid-tweets
tags:
- generated_from_trainer
model-index:
- name: movie_sentiment_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. -->

# movie_sentiment_trainer

This model is a fine-tuned version of [Sonny4Sonnix/twitter-roberta-base-sentimental-analysis-of-covid-tweets](https://huggingface.co/Sonny4Sonnix/twitter-roberta-base-sentimental-analysis-of-covid-tweets) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6934

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7168        | 0.2   | 500  | 0.6982          |
| 0.7017        | 0.4   | 1000 | 0.6971          |
| 0.6995        | 0.6   | 1500 | 0.7128          |
| 0.7027        | 0.8   | 2000 | 0.7011          |
| 0.7046        | 1.0   | 2500 | 0.6937          |
| 0.698         | 1.2   | 3000 | 0.6938          |
| 0.6988        | 1.4   | 3500 | 0.6932          |
| 0.6972        | 1.6   | 4000 | 0.6935          |
| 0.698         | 1.8   | 4500 | 0.6940          |
| 0.6975        | 2.0   | 5000 | 0.6973          |
| 0.6977        | 2.2   | 5500 | 0.6932          |
| 0.6955        | 2.4   | 6000 | 0.6933          |
| 0.6952        | 2.6   | 6500 | 0.6932          |
| 0.6946        | 2.8   | 7000 | 0.6941          |
| 0.6944        | 3.0   | 7500 | 0.6934          |


### Framework versions

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