---
base_model: readerbench/RoBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ro-sentiment-02
  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. -->

# ro-sentiment-02

This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4093
- Accuracy: 0.8312
- Precision: 0.8488
- Recall: 0.8866
- F1: 0.8673
- F1 Weighted: 0.8298

## 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: 6.3e-05
- train_batch_size: 96
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.25
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
| 0.4289        | 1.0   | 1086 | 0.4168          | 0.8303   | 0.8868    | 0.8570 | 0.8717 | 0.8317      |
| 0.3807        | 2.0   | 2172 | 0.3926          | 0.8424   | 0.8933    | 0.8680 | 0.8804 | 0.8434      |
| 0.3306        | 3.0   | 3258 | 0.4093          | 0.8312   | 0.8488    | 0.8866 | 0.8673 | 0.8298      |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3