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

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2251
- Accuracy: 0.9439
- Precision: 0.9422
- Recall: 0.9425
- F1: 0.9420

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9969        | 1.0   | 125  | 0.7141          | 0.7758   | 0.7913    | 0.7716 | 0.7652 |
| 0.7535        | 2.0   | 250  | 0.6724          | 0.8038   | 0.8426    | 0.8040 | 0.8019 |
| 0.6749        | 3.0   | 375  | 0.4999          | 0.8428   | 0.8615    | 0.8378 | 0.8410 |
| 0.4791        | 4.0   | 500  | 0.4593          | 0.8599   | 0.8766    | 0.8529 | 0.8562 |
| 0.4112        | 5.0   | 625  | 0.3726          | 0.8899   | 0.8925    | 0.8852 | 0.8852 |
| 0.3416        | 6.0   | 750  | 0.2770          | 0.9169   | 0.9137    | 0.9161 | 0.9133 |
| 0.3195        | 7.0   | 875  | 0.3013          | 0.9139   | 0.9163    | 0.9069 | 0.9096 |
| 0.1927        | 8.0   | 1000 | 0.2297          | 0.9369   | 0.9364    | 0.9344 | 0.9348 |
| 0.1596        | 9.0   | 1125 | 0.2510          | 0.9329   | 0.9344    | 0.9326 | 0.9324 |
| 0.1907        | 10.0  | 1250 | 0.2251          | 0.9439   | 0.9422    | 0.9425 | 0.9420 |


### Framework versions

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