---
license: mit
base_model: dumitrescustefan/bert-base-romanian-cased-v1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: sentiment-analysis-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. -->

# sentiment-analysis-model

This model is a fine-tuned version of [dumitrescustefan/bert-base-romanian-cased-v1](https://huggingface.co/dumitrescustefan/bert-base-romanian-cased-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2433
- Accuracy: 0.9151
- F1: 0.9151

## Intended uses & limitations

This model is intended to label reviews written in romanian as either **POSITIVE** or **NEGATIVE**.

## Training and evaluation data

Trained and evaluated using half of [ro_sent dataset](https://huggingface.co/datasets/ro_sent).

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 281  | 0.2449          | 0.9017   | 0.9020 |
| 0.2392        | 2.0   | 562  | 0.2433          | 0.9151   | 0.9151 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2