---
license: cc-by-4.0
library_name: peft
tags:
- generated_from_trainer
base_model: EMBEDDIA/crosloengual-bert
metrics:
- accuracy
- f1
model-index:
- name: loha_fine_tuned_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. -->

# loha_fine_tuned_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: 0.6890
- Accuracy: 0.52
- F1: 0.5212

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.7072        | 1.0   | 50   | 0.6896          | 0.52     | 0.5212 |
| 0.6973        | 2.0   | 100  | 0.6894          | 0.53     | 0.5312 |
| 0.6988        | 3.0   | 150  | 0.6892          | 0.54     | 0.5411 |
| 0.7016        | 4.0   | 200  | 0.6891          | 0.53     | 0.5312 |
| 0.7034        | 5.0   | 250  | 0.6890          | 0.52     | 0.5212 |
| 0.6978        | 6.0   | 300  | 0.6890          | 0.51     | 0.5112 |
| 0.6965        | 7.0   | 350  | 0.6890          | 0.51     | 0.5112 |
| 0.6907        | 8.0   | 400  | 0.6890          | 0.52     | 0.5212 |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1