---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sentiment_model
  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. -->

# sentiment_model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2038
- Accuracy: 0.9782
- Precision: 0.9791
- Recall: 0.9782
- F1: 0.9782

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2491        | 1.0   | 553  | 0.2143          | 0.95     | 0.9522    | 0.95   | 0.9499 |
| 0.1334        | 2.0   | 1106 | 0.1648          | 0.9679   | 0.9699    | 0.9679 | 0.9679 |
| 0.0002        | 3.0   | 1659 | 0.1815          | 0.9756   | 0.9768    | 0.9756 | 0.9756 |
| 0.0002        | 4.0   | 2212 | 0.2997          | 0.9615   | 0.9643    | 0.9615 | 0.9615 |
| 0.0001        | 5.0   | 2765 | 0.2159          | 0.9769   | 0.9779    | 0.9769 | 0.9769 |
| 0.0001        | 6.0   | 3318 | 0.2038          | 0.9782   | 0.9791    | 0.9782 | 0.9782 |


### Framework versions

- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1