---
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-convnextv2-nano-22k-384-finetuned-spiderTraining20-500
  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-nano-22k-384-finetuned-spiderTraining20-500

This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2966
- Accuracy: 0.9109
- Precision: 0.9058
- Recall: 0.9065
- F1: 0.9057

## 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: 25
- eval_batch_size: 25
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 100
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.7156        | 1.0   | 80   | 1.4314          | 0.6316   | 0.6182    | 0.6246 | 0.6155 |
| 0.7565        | 2.0   | 160  | 0.6340          | 0.8168   | 0.8213    | 0.8074 | 0.8095 |
| 0.5802        | 3.0   | 240  | 0.4632          | 0.8589   | 0.8566    | 0.8545 | 0.8539 |
| 0.4767        | 4.0   | 320  | 0.4006          | 0.8759   | 0.8748    | 0.8710 | 0.8708 |
| 0.3648        | 5.0   | 400  | 0.3529          | 0.8999   | 0.8976    | 0.8965 | 0.8960 |
| 0.3623        | 6.0   | 480  | 0.3326          | 0.9059   | 0.9030    | 0.9031 | 0.9024 |
| 0.3238        | 7.0   | 560  | 0.3178          | 0.8939   | 0.8910    | 0.8889 | 0.8892 |
| 0.2975        | 8.0   | 640  | 0.3016          | 0.9079   | 0.9037    | 0.9029 | 0.9028 |
| 0.2852        | 9.0   | 720  | 0.3090          | 0.9029   | 0.8979    | 0.8991 | 0.8974 |
| 0.2893        | 10.0  | 800  | 0.2966          | 0.9109   | 0.9058    | 0.9065 | 0.9057 |


### Framework versions

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