---
library_name: transformers
license: mit
base_model: dumitrescustefan/bert-base-romanian-cased-v1
tags:
- generated_from_trainer
datasets:
- moroco
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: teacher_moroco
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: moroco
      type: moroco
      config: moroco
      split: validation
      args: moroco
    metrics:
    - name: F1
      type: f1
      value: 0.8683940771433114
    - name: Accuracy
      type: accuracy
      value: 0.8485053200472893
    - name: Precision
      type: precision
      value: 0.8698117604818486
    - name: Recall
      type: recall
      value: 0.8672521533524743
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# teacher_moroco

This model is a fine-tuned version of [dumitrescustefan/bert-base-romanian-cased-v1](https://huggingface.co/dumitrescustefan/bert-base-romanian-cased-v1) on the moroco dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1075
- F1: 0.8684
- Roc Auc: 0.9149
- Accuracy: 0.8485
- Precision: 0.8698
- Recall: 0.8673

## 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: 16
- eval_batch_size: 16
- 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 | F1     | Roc Auc | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:---------:|:------:|
| 0.1332        | 1.0   | 1358 | 0.1120          | 0.8630 | 0.9075  | 0.8428   | 0.8822    | 0.8456 |
| 0.0935        | 2.0   | 2716 | 0.1075          | 0.8684 | 0.9149  | 0.8485   | 0.8698    | 0.8673 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0