---
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: twitter-roberta-base-sentiment-latest
  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. -->

# twitter-roberta-base-sentiment-latest

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3658
- Accuracy: 0.8045

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6116        | 0.2   | 100  | 0.4453          | 0.6965   |
| 0.4047        | 0.4   | 200  | 0.3999          | 0.735    |
| 0.3979        | 0.6   | 300  | 0.3641          | 0.7655   |
| 0.3828        | 0.8   | 400  | 0.3512          | 0.7635   |
| 0.3805        | 1.0   | 500  | 0.3489          | 0.776    |
| 0.3454        | 1.2   | 600  | 0.3488          | 0.774    |
| 0.3135        | 1.4   | 700  | 0.3529          | 0.785    |
| 0.3216        | 1.6   | 800  | 0.3344          | 0.7845   |
| 0.3005        | 1.8   | 900  | 0.3793          | 0.789    |
| 0.3041        | 2.0   | 1000 | 0.3324          | 0.7925   |
| 0.2126        | 2.2   | 1100 | 0.3839          | 0.7895   |
| 0.2218        | 2.4   | 1200 | 0.3653          | 0.7955   |
| 0.1986        | 2.6   | 1300 | 0.3745          | 0.803    |
| 0.2049        | 2.8   | 1400 | 0.3586          | 0.802    |
| 0.1911        | 3.0   | 1500 | 0.3658          | 0.8045   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1