---
license: apache-2.0
base_model: zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-finetuned-ausSpiders2000
  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. -->

# 10-finetuned-ausSpiders2000

This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co./zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0184
- Accuracy: 0.9929
- Precision: 0.9955
- Recall: 0.9910
- F1: 0.9932

## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2684        | 1.0   | 141  | 0.1271          | 0.9503   | 0.9350    | 0.9199 | 0.9198 |
| 0.1698        | 2.0   | 282  | 0.1668          | 0.9485   | 0.9229    | 0.9195 | 0.9123 |
| 0.1538        | 3.0   | 423  | 0.0906          | 0.9645   | 0.9764    | 0.9365 | 0.9523 |
| 0.153         | 4.0   | 564  | 0.0860          | 0.9707   | 0.9685    | 0.9451 | 0.9525 |
| 0.0699        | 5.0   | 705  | 0.0528          | 0.9813   | 0.9830    | 0.9728 | 0.9776 |
| 0.1107        | 6.0   | 846  | 0.0460          | 0.9831   | 0.9832    | 0.9879 | 0.9855 |
| 0.0647        | 7.0   | 987  | 0.0319          | 0.9849   | 0.9905    | 0.9765 | 0.9829 |
| 0.0461        | 8.0   | 1128 | 0.0350          | 0.9840   | 0.9866    | 0.9710 | 0.9776 |
| 0.0371        | 9.0   | 1269 | 0.0198          | 0.9920   | 0.9952    | 0.9903 | 0.9927 |
| 0.0496        | 10.0  | 1410 | 0.0184          | 0.9929   | 0.9955    | 0.9910 | 0.9932 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3