---
base_model: readerbench/RoBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: ro-sentiment-03
  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-03

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: 0.3923
- Accuracy: 0.8307
- Precision: 0.8366
- Recall: 0.8959
- F1: 0.8652
- F1 Weighted: 0.8287

## 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: 6e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------:|
| 0.4198        | 1.0   | 1629 | 0.3983          | 0.8377   | 0.8791    | 0.8721 | 0.8756 | 0.8380      |
| 0.3861        | 2.0   | 3258 | 0.4312          | 0.8429   | 0.8963    | 0.8665 | 0.8812 | 0.8442      |
| 0.3189        | 3.0   | 4887 | 0.3923          | 0.8307   | 0.8366    | 0.8959 | 0.8652 | 0.8287      |


### Framework versions

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