---
license: apache-2.0
base_model: google/bigbird-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bigbird-base-setup-multiple-choice
  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. -->

# bigbird-base-setup-multiple-choice

This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6931
- Accuracy: 0.5015
- Precision: 0.5015
- Recall: 0.5026
- F1: 0.5021

## 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: 1e-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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6946        | 1.0   | 1074 | 0.6931          | 0.5058   | 0.5062    | 0.4716 | 0.4883 |
| 0.694         | 2.0   | 2148 | 0.6931          | 0.5030   | 0.5032    | 0.4710 | 0.4865 |
| 0.6936        | 3.0   | 3222 | 0.6931          | 0.5015   | 0.5015    | 0.5026 | 0.5021 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0