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---
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
|