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---
license: cc-by-sa-4.0
base_model: EMBEDDIA/sloberta
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine_tuned_boolq_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_boolq_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: 1.8633
- Accuracy: 0.6111
- F1: 0.6255
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6442 | 4.1667 | 50 | 0.5523 | 0.7778 | 0.6806 |
| 0.3817 | 8.3333 | 100 | 1.0475 | 0.5556 | 0.5902 |
| 0.0355 | 12.5 | 150 | 1.4581 | 0.6111 | 0.6255 |
| 0.0098 | 16.6667 | 200 | 1.6364 | 0.6111 | 0.6255 |
| 0.0065 | 20.8333 | 250 | 1.8167 | 0.6111 | 0.6255 |
| 0.005 | 25.0 | 300 | 1.8363 | 0.6111 | 0.6255 |
| 0.0043 | 29.1667 | 350 | 1.8635 | 0.6111 | 0.6255 |
| 0.004 | 33.3333 | 400 | 1.8633 | 0.6111 | 0.6255 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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