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

This model is a fine-tuned version of [facebook/convnextv2-large-22k-384](https://huggingface.co./facebook/convnextv2-large-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0881
- Accuracy: 0.9740
- Precision: 0.9749
- Recall: 0.9729
- F1: 0.9733

## 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: 15
- eval_batch_size: 15
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 60
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5835        | 1.0   | 133  | 0.4317          | 0.8659   | 0.8765    | 0.8664 | 0.8594 |
| 0.3813        | 2.0   | 266  | 0.2008          | 0.9499   | 0.9533    | 0.9464 | 0.9488 |
| 0.3476        | 2.99  | 399  | 0.1535          | 0.9580   | 0.9591    | 0.9563 | 0.9570 |
| 0.1858        | 4.0   | 533  | 0.1591          | 0.9540   | 0.9542    | 0.9535 | 0.9532 |
| 0.1962        | 5.0   | 666  | 0.1356          | 0.9570   | 0.9565    | 0.9566 | 0.9556 |
| 0.1674        | 6.0   | 799  | 0.1290          | 0.9610   | 0.9612    | 0.9597 | 0.9599 |
| 0.1673        | 6.99  | 932  | 0.1138          | 0.9660   | 0.9669    | 0.9643 | 0.9651 |
| 0.1793        | 8.0   | 1066 | 0.0919          | 0.9720   | 0.9714    | 0.9707 | 0.9706 |
| 0.1369        | 9.0   | 1199 | 0.0936          | 0.9690   | 0.9690    | 0.9676 | 0.9677 |
| 0.1256        | 9.98  | 1330 | 0.0881          | 0.9740   | 0.9749    | 0.9729 | 0.9733 |


### Framework versions

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