---
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: finetuning-sentiment-model-tweet-OLDsamples
  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. -->

# finetuning-sentiment-model-tweet-OLDsamples

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: 1.3200
- Accuracy Percentage: 0.7738
- Accuracy Number: 65.0
- F1: 0.7878
- Precision: 0.7738
- Recall: 0.7738

## 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: 32
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy Percentage | Accuracy Number | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:---------------:|:------:|:---------:|:------:|
| 0.5465        | 1.0   | 11   | 0.5817          | 0.7857              | 66.0            | 0.7854 | 0.7857    | 0.7857 |
| 0.351         | 2.0   | 22   | 0.4817          | 0.7976              | 67.0            | 0.7930 | 0.7976    | 0.7976 |
| 0.1612        | 3.0   | 33   | 1.0279          | 0.75                | 63.0            | 0.7618 | 0.75      | 0.75   |
| 0.0734        | 4.0   | 44   | 1.0266          | 0.7857              | 66.0            | 0.7968 | 0.7857    | 0.7857 |
| 0.0303        | 5.0   | 55   | 0.8942          | 0.8095              | 68.0            | 0.8150 | 0.8095    | 0.8095 |
| 0.0083        | 6.0   | 66   | 1.1278          | 0.8095              | 68.0            | 0.8177 | 0.8095    | 0.8095 |
| 0.0028        | 7.0   | 77   | 1.2560          | 0.7738              | 65.0            | 0.7878 | 0.7738    | 0.7738 |
| 0.0012        | 8.0   | 88   | 1.2988          | 0.7738              | 65.0            | 0.7878 | 0.7738    | 0.7738 |
| 0.001         | 9.0   | 99   | 1.3170          | 0.7857              | 66.0            | 0.7997 | 0.7857    | 0.7857 |
| 0.001         | 10.0  | 110  | 1.3200          | 0.7738              | 65.0            | 0.7878 | 0.7738    | 0.7738 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3