---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-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-finetuned-spiderTraining50-200

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: 0.3858
- Accuracy: 0.8899
- Precision: 0.8906
- Recall: 0.8904
- F1: 0.8882

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6006        | 1.0   | 125  | 1.3292          | 0.6246   | 0.6998    | 0.6230 | 0.6169 |
| 1.3122        | 2.0   | 250  | 1.0785          | 0.6747   | 0.7123    | 0.6769 | 0.6664 |
| 0.8869        | 3.0   | 375  | 0.9295          | 0.7367   | 0.7838    | 0.7398 | 0.7424 |
| 0.7394        | 4.0   | 500  | 0.6719          | 0.8078   | 0.8157    | 0.8089 | 0.8041 |
| 0.5704        | 5.0   | 625  | 0.6200          | 0.8198   | 0.8320    | 0.8265 | 0.8176 |
| 0.4273        | 6.0   | 750  | 0.5874          | 0.8338   | 0.8469    | 0.8338 | 0.8310 |
| 0.3289        | 7.0   | 875  | 0.5009          | 0.8549   | 0.8618    | 0.8523 | 0.8519 |
| 0.2828        | 8.0   | 1000 | 0.4697          | 0.8699   | 0.8728    | 0.8696 | 0.8677 |
| 0.2991        | 9.0   | 1125 | 0.4464          | 0.8639   | 0.8651    | 0.8653 | 0.8609 |
| 0.2108        | 10.0  | 1250 | 0.3858          | 0.8899   | 0.8906    | 0.8904 | 0.8882 |


### Framework versions

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