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---
license: apache-2.0
base_model: zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-finetuned-taiwanSpiders
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-taiwanSpiders
This model is a fine-tuned version of [zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000](https://huggingface.co./zkdeng/10-convnextv2-base-22k-384-finetuned-spiderTraining1000-1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2014
- Accuracy: 0.9486
- Precision: 0.9408
- Recall: 0.9397
- F1: 0.9395
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6309 | 1.0 | 759 | 0.4255 | 0.8779 | 0.8669 | 0.8560 | 0.8499 |
| 0.6529 | 2.0 | 1519 | 0.3880 | 0.8882 | 0.8728 | 0.8710 | 0.8634 |
| 0.53 | 3.0 | 2278 | 0.3389 | 0.9024 | 0.8953 | 0.8929 | 0.8896 |
| 0.4746 | 4.0 | 3038 | 0.3393 | 0.9017 | 0.9036 | 0.8868 | 0.8881 |
| 0.4565 | 5.0 | 3797 | 0.3061 | 0.9169 | 0.9266 | 0.9044 | 0.9094 |
| 0.3145 | 6.0 | 4557 | 0.2600 | 0.9282 | 0.9237 | 0.9148 | 0.9173 |
| 0.3034 | 7.0 | 5316 | 0.2613 | 0.9345 | 0.9306 | 0.9216 | 0.9225 |
| 0.2724 | 8.0 | 6076 | 0.2410 | 0.9417 | 0.9371 | 0.9312 | 0.9319 |
| 0.2055 | 9.0 | 6835 | 0.2127 | 0.9457 | 0.9382 | 0.9378 | 0.9370 |
| 0.2103 | 9.99 | 7590 | 0.2014 | 0.9486 | 0.9408 | 0.9397 | 0.9395 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
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