---
license: apache-2.0
base_model: facebook/convnextv2-huge-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-convnextv2-huge-22k-384-finetuned-spiderTraining20-500
  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-convnextv2-huge-22k-384-finetuned-spiderTraining20-500

This model is a fine-tuned version of [facebook/convnextv2-huge-22k-384](https://huggingface.co/facebook/convnextv2-huge-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0908
- Accuracy: 0.9830
- Precision: 0.9830
- Recall: 0.9833
- F1: 0.9830

## 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: 5
- eval_batch_size: 5
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4733        | 1.0   | 399  | 0.2998          | 0.9149   | 0.9195    | 0.9099 | 0.9121 |
| 0.3925        | 2.0   | 799  | 0.1649          | 0.9510   | 0.9512    | 0.9502 | 0.9498 |
| 0.3932        | 3.0   | 1199 | 0.4475          | 0.8689   | 0.9166    | 0.8633 | 0.8785 |
| 0.2441        | 4.0   | 1599 | 0.1623          | 0.9469   | 0.9519    | 0.9449 | 0.9462 |
| 0.1249        | 5.0   | 1998 | 0.1646          | 0.9570   | 0.9609    | 0.9546 | 0.9565 |
| 0.2255        | 6.0   | 2398 | 0.1560          | 0.9660   | 0.9666    | 0.9644 | 0.9646 |
| 0.1426        | 7.0   | 2798 | 0.1115          | 0.9720   | 0.9741    | 0.9725 | 0.9731 |
| 0.102         | 8.0   | 3198 | 0.0927          | 0.9750   | 0.9754    | 0.9757 | 0.9754 |
| 0.0663        | 9.0   | 3597 | 0.0894          | 0.9820   | 0.9826    | 0.9821 | 0.9821 |
| 0.0556        | 9.98  | 3990 | 0.0908          | 0.9830   | 0.9830    | 0.9833 | 0.9830 |


### Framework versions

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