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---
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
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