---
license: mit
tags:
- generated_from_trainer
model-index:
- name: finetuned-Sentiment-classfication-ROBERTA-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. -->

# finetuned-Sentiment-classfication-ROBERTA-model

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5618
- Rmse: 0.6118

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7273        | 2.0   | 500  | 0.5618          | 0.6118 |
| 0.4294        | 4.0   | 1000 | 0.5821          | 0.5906 |
| 0.2278        | 6.0   | 1500 | 0.8019          | 0.6235 |
| 0.1246        | 8.0   | 2000 | 0.9412          | 0.5961 |
| 0.083         | 10.0  | 2500 | 1.1040          | 0.5978 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3