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---
license: apache-2.0
base_model: facebook/convnextv2-huge-22k-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-convnextv2-huge-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-huge-22k-384-finetuned-spiderTraining20-500
This model is a fine-tuned version of [facebook/convnextv2-huge-22k-384](https://huggingface.co./facebook/convnextv2-huge-22k-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0908
- Accuracy: 0.9830
- Precision: 0.9830
- Recall: 0.9833
- F1: 0.9830
## 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: 5
- eval_batch_size: 5
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4733 | 1.0 | 399 | 0.2998 | 0.9149 | 0.9195 | 0.9099 | 0.9121 |
| 0.3925 | 2.0 | 799 | 0.1649 | 0.9510 | 0.9512 | 0.9502 | 0.9498 |
| 0.3932 | 3.0 | 1199 | 0.4475 | 0.8689 | 0.9166 | 0.8633 | 0.8785 |
| 0.2441 | 4.0 | 1599 | 0.1623 | 0.9469 | 0.9519 | 0.9449 | 0.9462 |
| 0.1249 | 5.0 | 1998 | 0.1646 | 0.9570 | 0.9609 | 0.9546 | 0.9565 |
| 0.2255 | 6.0 | 2398 | 0.1560 | 0.9660 | 0.9666 | 0.9644 | 0.9646 |
| 0.1426 | 7.0 | 2798 | 0.1115 | 0.9720 | 0.9741 | 0.9725 | 0.9731 |
| 0.102 | 8.0 | 3198 | 0.0927 | 0.9750 | 0.9754 | 0.9757 | 0.9754 |
| 0.0663 | 9.0 | 3597 | 0.0894 | 0.9820 | 0.9826 | 0.9821 | 0.9821 |
| 0.0556 | 9.98 | 3990 | 0.0908 | 0.9830 | 0.9830 | 0.9833 | 0.9830 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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