---
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-ausSpiders
  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-ausSpiders

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: 0.0399
- Accuracy: 0.9896
- Precision: 0.9831
- Recall: 0.9577
- F1: 0.9683

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1696        | 1.0   | 767  | 0.1719          | 0.9477   | 0.9104    | 0.8399 | 0.8558 |
| 0.114         | 2.0   | 1534 | 0.0823          | 0.9754   | 0.9637    | 0.8941 | 0.9185 |
| 0.1065        | 3.0   | 2301 | 0.0857          | 0.9708   | 0.8828    | 0.8472 | 0.8572 |
| 0.112         | 4.0   | 3069 | 0.0781          | 0.9756   | 0.9361    | 0.8767 | 0.8803 |
| 0.1006        | 5.0   | 3836 | 0.0610          | 0.9821   | 0.9662    | 0.9362 | 0.9485 |
| 0.0838        | 6.0   | 4603 | 0.0571          | 0.9817   | 0.9397    | 0.9442 | 0.9380 |
| 0.0766        | 7.0   | 5370 | 0.0507          | 0.9832   | 0.9626    | 0.9175 | 0.9302 |
| 0.0523        | 8.0   | 6138 | 0.0398          | 0.9870   | 0.9470    | 0.9763 | 0.9577 |
| 0.0531        | 9.0   | 6905 | 0.0456          | 0.9892   | 0.9881    | 0.9556 | 0.9697 |
| 0.0419        | 10.0  | 7670 | 0.0399          | 0.9896   | 0.9831    | 0.9577 | 0.9683 |


### Framework versions

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