---
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-spiderTraining1000-1000
  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-spiderTraining1000-1000

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: 0.3586
- Accuracy: 0.9180
- Precision: 0.9196
- Recall: 0.9160
- F1: 0.9168

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.0397        | 1.0   | 4064  | 1.4192          | 0.6356   | 0.6956    | 0.6130 | 0.6167 |
| 1.3997        | 2.0   | 8129  | 0.9638          | 0.7454   | 0.7708    | 0.7320 | 0.7325 |
| 1.1393        | 3.0   | 12193 | 0.7564          | 0.7973   | 0.8102    | 0.7883 | 0.7884 |
| 0.9942        | 4.0   | 16258 | 0.6256          | 0.8331   | 0.8464    | 0.8276 | 0.8294 |
| 0.8572        | 5.0   | 20322 | 0.5610          | 0.8507   | 0.8632    | 0.8441 | 0.8467 |
| 0.6445        | 6.0   | 24387 | 0.4866          | 0.8730   | 0.8802    | 0.8688 | 0.8697 |
| 0.5444        | 7.0   | 28451 | 0.4496          | 0.8852   | 0.8909    | 0.8812 | 0.8829 |
| 0.4955        | 8.0   | 32516 | 0.4241          | 0.8986   | 0.9039    | 0.8952 | 0.8974 |
| 0.448         | 9.0   | 36580 | 0.3875          | 0.9104   | 0.9133    | 0.9078 | 0.9091 |
| 0.4109        | 10.0  | 40640 | 0.3586          | 0.9180   | 0.9196    | 0.9160 | 0.9168 |


### Framework versions

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