---
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-spiderTraining100-100
  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-spiderTraining100-100

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: 1.3480
- Accuracy: 0.708
- Precision: 0.7226
- Recall: 0.7142
- F1: 0.6994

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 3.5765        | 1.0   | 125  | 3.3326          | 0.293    | 0.3422    | 0.2932 | 0.2604 |
| 2.29          | 2.0   | 250  | 2.1112          | 0.539    | 0.5769    | 0.5460 | 0.5180 |
| 1.8212        | 3.0   | 375  | 1.6097          | 0.657    | 0.6790    | 0.6674 | 0.6465 |
| 1.4779        | 4.0   | 500  | 1.4234          | 0.688    | 0.7060    | 0.6974 | 0.6802 |
| 1.3378        | 5.0   | 625  | 1.3480          | 0.708    | 0.7226    | 0.7142 | 0.6994 |


### Framework versions

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