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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google-bert/bert-base-uncased
metrics:
- accuracy
- f1
model-index:
- name: loha_fine_tuned_boolq
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
This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5655
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6686 | 4.1667 | 50 | 0.6058 | 0.7778 | 0.6806 |
| 0.661 | 8.3333 | 100 | 0.5835 | 0.7778 | 0.6806 |
| 0.66 | 12.5 | 150 | 0.5765 | 0.7778 | 0.6806 |
| 0.6685 | 16.6667 | 200 | 0.5708 | 0.7778 | 0.6806 |
| 0.6634 | 20.8333 | 250 | 0.5677 | 0.7778 | 0.6806 |
| 0.6573 | 25.0 | 300 | 0.5668 | 0.7778 | 0.6806 |
| 0.6623 | 29.1667 | 350 | 0.5661 | 0.7778 | 0.6806 |
| 0.6583 | 33.3333 | 400 | 0.5655 | 0.7778 | 0.6806 |
### Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.40.1
- Pytorch 2.1.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1 |