---
license: apache-2.0
base_model: google/bigbird-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bigbird-roberta-base-finetuned-sql-classification-with_schema_question
  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-roberta-base-finetuned-sql-classification-with_schema_question

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: 0.4232
- Accuracy: 0.8337
- F1: 0.8617
- Precision: 0.7971
- Recall: 0.9375

## 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: 5e-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
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6156        | 1.0   | 1290 | 0.4973          | 0.7767   | 0.8292 | 0.7180    | 0.9811 |
| 0.4798        | 2.0   | 2580 | 0.4877          | 0.7860   | 0.8358 | 0.7253    | 0.9860 |
| 0.4841        | 3.0   | 3870 | 0.4767          | 0.7969   | 0.8400 | 0.7434    | 0.9656 |
| 0.4573        | 4.0   | 5160 | 0.4716          | 0.8225   | 0.8513 | 0.7921    | 0.92   |
| 0.4048        | 5.0   | 6450 | 0.4232          | 0.8337   | 0.8617 | 0.7971    | 0.9375 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2