|
--- |
|
license: cc-by-sa-4.0 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: EMBEDDIA/sloberta |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: loha_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. --> |
|
|
|
# loha_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: 0.5638 |
|
- Accuracy: 0.7778 |
|
- F1: 0.6806 |
|
|
|
## 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 | |
|
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
|
| 0.6734 | 4.1667 | 50 | 0.5813 | 0.7778 | 0.6806 | |
|
| 0.6547 | 8.3333 | 100 | 0.5652 | 0.7778 | 0.6806 | |
|
| 0.6498 | 12.5 | 150 | 0.5666 | 0.7778 | 0.6806 | |
|
| 0.655 | 16.6667 | 200 | 0.5663 | 0.7778 | 0.6806 | |
|
| 0.6529 | 20.8333 | 250 | 0.5649 | 0.7778 | 0.6806 | |
|
| 0.6517 | 25.0 | 300 | 0.5633 | 0.7778 | 0.6806 | |
|
| 0.655 | 29.1667 | 350 | 0.5641 | 0.7778 | 0.6806 | |
|
| 0.6521 | 33.3333 | 400 | 0.5638 | 0.7778 | 0.6806 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.40.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
