---
license: cc-by-sa-4.0
base_model: EMBEDDIA/sloberta
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_rte_sloberta
  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. -->

# fine_tuned_rte_sloberta

This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6898
- Accuracy: 0.6897
- F1: 0.6912

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.7035        | 1.7241  | 50   | 0.7322          | 0.4138   | 0.2422 |
| 0.7032        | 3.4483  | 100  | 0.6935          | 0.4138   | 0.2422 |
| 0.6998        | 5.1724  | 150  | 0.7021          | 0.4138   | 0.2422 |
| 0.697         | 6.8966  | 200  | 0.6828          | 0.5862   | 0.4333 |
| 0.6968        | 8.6207  | 250  | 0.6837          | 0.5862   | 0.4333 |
| 0.6965        | 10.3448 | 300  | 0.6897          | 0.5862   | 0.4333 |
| 0.6934        | 12.0690 | 350  | 0.6869          | 0.5862   | 0.4333 |
| 0.6878        | 13.7931 | 400  | 0.6898          | 0.6897   | 0.6912 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1