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---
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 |