---
library_name: transformers
language:
- en
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-sentiment
  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. -->

# roberta-base-finetuned-sentiment

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb-dataset-of-50k-movie-reviews dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2595
- Accuracy: 0.9495

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2815        | 1.0   | 1250 | 0.1705          | 0.9366   |
| 0.1358        | 2.0   | 2500 | 0.1550          | 0.9463   |
| 0.0879        | 3.0   | 3750 | 0.2081          | 0.947    |
| 0.0564        | 4.0   | 5000 | 0.2479          | 0.9474   |
| 0.0339        | 5.0   | 6250 | 0.2595          | 0.9495   |


### Framework versions

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