---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- circa
metrics:
- accuracy
model-index:
- name: BERT_QandA
  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: 0.8764964388543719
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERT_QandA

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the circa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4298
- Accuracy: 0.8765

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5797        | 1.0   | 619  | 0.4172          | 0.8532   |
| 0.3531        | 2.0   | 1238 | 0.3885          | 0.8735   |
| 0.2334        | 3.0   | 1857 | 0.4298          | 0.8765   |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0.dev20230220
- Datasets 2.10.0
- Tokenizers 0.11.0