---
tags:
- generated_from_trainer
datasets:
- circa
metrics:
- accuracy
model-index:
- name: BERT_BOOLQ_Circa_YN
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: circa
      type: circa
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9090771328989241
---

<!-- 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. -->

# BERT_BOOLQ_Circa_YN

This model is a fine-tuned version of [lewtun/bert-large-uncased-wwm-finetuned-boolq](https://huggingface.co/lewtun/bert-large-uncased-wwm-finetuned-boolq) on the circa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3944
- Accuracy: 0.9091

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5055        | 1.0   | 619  | 0.3336          | 0.8868   |
| 0.2832        | 2.0   | 1238 | 0.3039          | 0.9100   |
| 0.1729        | 3.0   | 1857 | 0.3944          | 0.9091   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2