---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: RoBERTa-finetuned-hotel-reviews-sentiment-analysis
  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-finetuned-hotel-reviews-sentiment-analysis

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0302
- Accuracy: 0.6897
- F1: 0.6440
- Precision: 0.6477
- Recall: 0.6406

## 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 OptimizerNames.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: 175
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9111        | 1.0   | 513  | 0.7323          | 0.6824   | 0.6337 | 0.6216    | 0.6508 |
| 0.671         | 2.0   | 1026 | 0.7124          | 0.6868   | 0.6362 | 0.6513    | 0.6288 |
| 0.5637        | 3.0   | 1539 | 0.7307          | 0.7007   | 0.6401 | 0.6548    | 0.6312 |
| 0.4554        | 4.0   | 2052 | 0.8162          | 0.6946   | 0.6431 | 0.6396    | 0.6501 |
| 0.344         | 5.0   | 2565 | 0.9359          | 0.6919   | 0.6424 | 0.6511    | 0.6374 |
| 0.2628        | 6.0   | 3078 | 1.0302          | 0.6897   | 0.6440 | 0.6477    | 0.6406 |


### Framework versions

- Transformers 4.54.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2