---
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-spiderTraining100-1000
  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-spiderTraining100-1000

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: 0.2678
- Accuracy: 0.9313
- Precision: 0.9311
- Recall: 0.9308
- F1: 0.9305

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.4003        | 1.0   | 740  | 1.0372          | 0.7086   | 0.7534    | 0.7061 | 0.7057 |
| 1.157         | 2.0   | 1481 | 0.7866          | 0.7733   | 0.8025    | 0.7714 | 0.7726 |
| 0.9605        | 3.0   | 2222 | 0.5709          | 0.8352   | 0.8458    | 0.8346 | 0.8345 |
| 0.7619        | 4.0   | 2963 | 0.4979          | 0.8576   | 0.8659    | 0.8563 | 0.8571 |
| 0.6643        | 5.0   | 3703 | 0.4230          | 0.8807   | 0.8870    | 0.8794 | 0.8797 |
| 0.5426        | 6.0   | 4444 | 0.3959          | 0.8898   | 0.8938    | 0.8889 | 0.8887 |
| 0.5035        | 7.0   | 5185 | 0.3426          | 0.9041   | 0.9063    | 0.9038 | 0.9034 |
| 0.3408        | 8.0   | 5926 | 0.3108          | 0.9188   | 0.9198    | 0.9179 | 0.9180 |
| 0.348         | 9.0   | 6666 | 0.2885          | 0.9238   | 0.9245    | 0.9230 | 0.9230 |
| 0.3402        | 9.99  | 7400 | 0.2678          | 0.9313   | 0.9311    | 0.9308 | 0.9305 |


### Framework versions

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