---
library_name: transformers
base_model: cardiffnlp/twitter-roberta-base-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
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 [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2791
- Accuracy: 0.794
- F1: 0.7938
- Precision: 0.7958
- Recall: 0.7986

## 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: 128
- eval_batch_size: 64
- 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4814        | 1.0   | 55   | 0.5014          | 0.793    | 0.7925 | 0.7935    | 0.8008 |
| 0.3957        | 2.0   | 110  | 0.5091          | 0.806    | 0.8050 | 0.8120    | 0.8030 |
| 0.2667        | 3.0   | 165  | 0.6027          | 0.815    | 0.8149 | 0.8195    | 0.8148 |
| 0.1823        | 4.0   | 220  | 0.7652          | 0.802    | 0.8015 | 0.8021    | 0.8088 |
| 0.1114        | 5.0   | 275  | 0.8443          | 0.808    | 0.8080 | 0.8105    | 0.8117 |
| 0.0862        | 6.0   | 330  | 0.9307          | 0.802    | 0.8021 | 0.8043    | 0.8072 |
| 0.0422        | 7.0   | 385  | 1.0603          | 0.792    | 0.7919 | 0.7943    | 0.7958 |
| 0.0323        | 8.0   | 440  | 1.1902          | 0.793    | 0.7928 | 0.7948    | 0.7982 |
| 0.0195        | 9.0   | 495  | 1.2363          | 0.791    | 0.7909 | 0.7941    | 0.7941 |
| 0.0172        | 10.0  | 550  | 1.2791          | 0.794    | 0.7938 | 0.7958    | 0.7986 |


### Framework versions

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