metadata
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: []
bigbird-roberta-base-finetuned-sql-classification-with_schema_question
This model is a fine-tuned version of 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