---
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: 3-10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000-finetuned-spiderTraining100-1000
  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. -->

# 3-10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000-finetuned-spiderTraining100-1000

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: 0.1305
- Accuracy: 0.9623
- Precision: 0.9628
- Recall: 0.9625
- F1: 0.9623

## 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: 27
- eval_batch_size: 27
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 108
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.558         | 1.0   | 740  | 0.2587          | 0.9239   | 0.9277    | 0.9235 | 0.9238 |
| 0.4179        | 2.0   | 1481 | 0.1747          | 0.9482   | 0.9493    | 0.9488 | 0.9483 |
| 0.3482        | 3.0   | 2220 | 0.1305          | 0.9623   | 0.9628    | 0.9625 | 0.9623 |


### Framework versions

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