|
--- |
|
license: cc-by-sa-4.0 |
|
base_model: EMBEDDIA/sloberta |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: 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. --> |
|
|
|
# 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: 0.6620 |
|
- Accuracy: 0.6217 |
|
- F1: 0.4767 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
|
| 0.6784 | 0.0424 | 50 | 0.6646 | 0.6217 | 0.4767 | |
|
| 0.6768 | 0.0848 | 100 | 0.6692 | 0.6217 | 0.4767 | |
|
| 0.6872 | 0.1272 | 150 | 0.6740 | 0.6217 | 0.4767 | |
|
| 0.6597 | 0.1696 | 200 | 0.6676 | 0.6217 | 0.4767 | |
|
| 0.664 | 0.2120 | 250 | 0.6641 | 0.6217 | 0.4767 | |
|
| 0.654 | 0.2545 | 300 | 0.6656 | 0.6217 | 0.4767 | |
|
| 0.6709 | 0.2969 | 350 | 0.6621 | 0.6217 | 0.4767 | |
|
| 0.6815 | 0.3393 | 400 | 0.6620 | 0.6217 | 0.4767 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|