---
license: cc-by-4.0
base_model: EMBEDDIA/crosloengual-bert
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_rte_croslo
  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_croslo

This model is a fine-tuned version of [EMBEDDIA/crosloengual-bert](https://huggingface.co/EMBEDDIA/crosloengual-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6954
- Accuracy: 0.6207
- F1: 0.6090

## 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: 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     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6763        | 1.7241  | 50   | 0.7138          | 0.4483   | 0.4145 |
| 0.5789        | 3.4483  | 100  | 0.6502          | 0.5517   | 0.5215 |
| 0.4644        | 5.1724  | 150  | 0.6409          | 0.6552   | 0.6552 |
| 0.3137        | 6.8966  | 200  | 0.6524          | 0.5862   | 0.5222 |
| 0.2053        | 8.6207  | 250  | 0.6379          | 0.6552   | 0.6388 |
| 0.1242        | 10.3448 | 300  | 0.6661          | 0.6207   | 0.6090 |
| 0.0737        | 12.0690 | 350  | 0.6753          | 0.6207   | 0.6090 |
| 0.0521        | 13.7931 | 400  | 0.6954          | 0.6207   | 0.6090 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1