---
library_name: transformers
license: mit
base_model: dumitrescustefan/bert-base-romanian-cased-v1
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: teacher_sst2
  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. -->

# teacher_sst2

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: 0.5451
- F1: 0.8648
- Roc Auc: 0.8646
- Accuracy: 0.8635

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3669        | 1.0   | 1053 | 0.4399          | 0.8248 | 0.8238  | 0.8211   |
| 0.2433        | 2.0   | 2106 | 0.4043          | 0.8457 | 0.8458  | 0.8417   |
| 0.1811        | 3.0   | 3159 | 0.4268          | 0.8625 | 0.8622  | 0.8612   |
| 0.1373        | 4.0   | 4212 | 0.4359          | 0.8537 | 0.8545  | 0.8521   |
| 0.1157        | 5.0   | 5265 | 0.4812          | 0.8681 | 0.8684  | 0.8681   |
| 0.0949        | 6.0   | 6318 | 0.5003          | 0.8607 | 0.8604  | 0.8601   |
| 0.0774        | 7.0   | 7371 | 0.5142          | 0.8643 | 0.8641  | 0.8624   |
| 0.0713        | 8.0   | 8424 | 0.5451          | 0.8648 | 0.8646  | 0.8635   |


### Framework versions

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