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

# prompt_fine_tuned_boolq_googlemt_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: 0.6648
- Accuracy: 0.6187
- F1: 0.4828

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.702         | 0.0424 | 50   | 0.6852          | 0.5856   | 0.5231 |
| 0.6764        | 0.0848 | 100  | 0.6712          | 0.6061   | 0.5086 |
| 0.6879        | 0.1272 | 150  | 0.6696          | 0.6052   | 0.5037 |
| 0.6585        | 0.1696 | 200  | 0.6670          | 0.6116   | 0.4966 |
| 0.6559        | 0.2120 | 250  | 0.6655          | 0.6107   | 0.5001 |
| 0.6648        | 0.2545 | 300  | 0.6649          | 0.6138   | 0.4849 |
| 0.6715        | 0.2969 | 350  | 0.6648          | 0.6190   | 0.4834 |
| 0.6773        | 0.3393 | 400  | 0.6648          | 0.6187   | 0.4828 |


### Framework versions

- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1