---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 20-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. -->

# 20-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: 0.4409
- Accuracy: 0.8909
- Precision: 0.8899
- Recall: 0.8922
- F1: 0.8881

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.4597        | 1.0   | 125  | 1.1828          | 0.6617   | 0.7065    | 0.6632 | 0.6495 |
| 1.2938        | 2.0   | 250  | 1.0667          | 0.6827   | 0.7244    | 0.6845 | 0.6701 |
| 1.1316        | 3.0   | 375  | 0.9465          | 0.7257   | 0.7828    | 0.7291 | 0.7280 |
| 0.7827        | 4.0   | 500  | 0.8576          | 0.7397   | 0.7701    | 0.7394 | 0.7372 |
| 0.7407        | 5.0   | 625  | 0.8084          | 0.7728   | 0.7876    | 0.7728 | 0.7636 |
| 0.6481        | 6.0   | 750  | 0.7537          | 0.7798   | 0.7999    | 0.7783 | 0.7765 |
| 0.5868        | 7.0   | 875  | 0.6406          | 0.8258   | 0.8341    | 0.8266 | 0.8224 |
| 0.4461        | 8.0   | 1000 | 0.7555          | 0.7768   | 0.7953    | 0.7736 | 0.7679 |
| 0.4984        | 9.0   | 1125 | 0.6601          | 0.8128   | 0.8260    | 0.8120 | 0.8059 |
| 0.3898        | 10.0  | 1250 | 0.7017          | 0.8108   | 0.8296    | 0.8079 | 0.8059 |
| 0.3262        | 11.0  | 1375 | 0.6199          | 0.8258   | 0.8341    | 0.8268 | 0.8212 |
| 0.3243        | 12.0  | 1500 | 0.6561          | 0.8188   | 0.8316    | 0.8256 | 0.8191 |
| 0.2914        | 13.0  | 1625 | 0.6037          | 0.8368   | 0.8504    | 0.8429 | 0.8351 |
| 0.2627        | 14.0  | 1750 | 0.5609          | 0.8529   | 0.8588    | 0.8557 | 0.8501 |
| 0.2457        | 15.0  | 1875 | 0.5266          | 0.8639   | 0.8674    | 0.8666 | 0.8613 |
| 0.2294        | 16.0  | 2000 | 0.5475          | 0.8589   | 0.8658    | 0.8608 | 0.8560 |
| 0.2088        | 17.0  | 2125 | 0.4929          | 0.8699   | 0.8726    | 0.8678 | 0.8672 |
| 0.2101        | 18.0  | 2250 | 0.4488          | 0.8799   | 0.8782    | 0.8775 | 0.8752 |
| 0.1767        | 19.0  | 2375 | 0.4543          | 0.8829   | 0.8824    | 0.8808 | 0.8782 |
| 0.1445        | 20.0  | 2500 | 0.4409          | 0.8909   | 0.8899    | 0.8922 | 0.8881 |


### Framework versions

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