---
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-taiwanSpiders
  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-taiwanSpiders

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: 0.2014
- Accuracy: 0.9486
- Precision: 0.9408
- Recall: 0.9397
- F1: 0.9395

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6309        | 1.0   | 759  | 0.4255          | 0.8779   | 0.8669    | 0.8560 | 0.8499 |
| 0.6529        | 2.0   | 1519 | 0.3880          | 0.8882   | 0.8728    | 0.8710 | 0.8634 |
| 0.53          | 3.0   | 2278 | 0.3389          | 0.9024   | 0.8953    | 0.8929 | 0.8896 |
| 0.4746        | 4.0   | 3038 | 0.3393          | 0.9017   | 0.9036    | 0.8868 | 0.8881 |
| 0.4565        | 5.0   | 3797 | 0.3061          | 0.9169   | 0.9266    | 0.9044 | 0.9094 |
| 0.3145        | 6.0   | 4557 | 0.2600          | 0.9282   | 0.9237    | 0.9148 | 0.9173 |
| 0.3034        | 7.0   | 5316 | 0.2613          | 0.9345   | 0.9306    | 0.9216 | 0.9225 |
| 0.2724        | 8.0   | 6076 | 0.2410          | 0.9417   | 0.9371    | 0.9312 | 0.9319 |
| 0.2055        | 9.0   | 6835 | 0.2127          | 0.9457   | 0.9382    | 0.9378 | 0.9370 |
| 0.2103        | 9.99  | 7590 | 0.2014          | 0.9486   | 0.9408    | 0.9397 | 0.9395 |


### Framework versions

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