---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-convnextv2-base-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. -->

# 10-convnextv2-base-22k-384-finetuned-spiderTraining50-200

This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2953
- Accuracy: 0.9179
- Precision: 0.9143
- Recall: 0.9169
- F1: 0.9135

## 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: 27
- eval_batch_size: 27
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 108
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2896        | 1.0   | 74   | 0.9797          | 0.7057   | 0.7360    | 0.7011 | 0.6843 |
| 1.1398        | 1.99  | 148  | 0.9558          | 0.7227   | 0.7691    | 0.7254 | 0.7197 |
| 0.7899        | 2.99  | 222  | 0.6987          | 0.7948   | 0.8101    | 0.7890 | 0.7866 |
| 0.5357        | 4.0   | 297  | 0.6526          | 0.8148   | 0.8327    | 0.8161 | 0.8104 |
| 0.4807        | 5.0   | 371  | 0.5543          | 0.8398   | 0.8512    | 0.8407 | 0.8367 |
| 0.3575        | 5.99  | 445  | 0.4465          | 0.8789   | 0.8814    | 0.8790 | 0.8746 |
| 0.3728        | 6.99  | 519  | 0.4344          | 0.8819   | 0.8840    | 0.8794 | 0.8772 |
| 0.2892        | 8.0   | 594  | 0.3911          | 0.8859   | 0.8879    | 0.8839 | 0.8804 |
| 0.2082        | 9.0   | 668  | 0.3256          | 0.9079   | 0.9067    | 0.9091 | 0.9053 |
| 0.1737        | 9.97  | 740  | 0.2953          | 0.9179   | 0.9143    | 0.9169 | 0.9135 |


### Framework versions

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