---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-tiny-22k-384-finetuned-spiderTraining50-200
  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. -->

# convnextv2-tiny-22k-384-finetuned-spiderTraining50-200

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: 0.6618
- Accuracy: 0.8408
- Precision: 0.8430
- Recall: 0.8393
- F1: 0.8361

## 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: 16
- eval_batch_size: 16
- seed: 42
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2156        | 1.0   | 125  | 1.9182          | 0.6036   | 0.6139    | 0.5965 | 0.5754 |
| 1.2471        | 2.0   | 250  | 1.0718          | 0.7427   | 0.7609    | 0.7412 | 0.7358 |
| 0.9458        | 3.0   | 375  | 0.7971          | 0.7998   | 0.8151    | 0.7983 | 0.7968 |
| 0.7643        | 4.0   | 500  | 0.6945          | 0.8318   | 0.8318    | 0.8304 | 0.8272 |
| 0.7085        | 5.0   | 625  | 0.6618          | 0.8408   | 0.8430    | 0.8393 | 0.8361 |


### Framework versions

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