Model save
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README.md
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---
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license: apache-2.0
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base_model: facebook/convnextv2-tiny-22k-384
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: 10-finetuned-spiderTraining20-500
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# 10-finetuned-spiderTraining20-500
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.2251
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- Accuracy: 0.9439
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- Precision: 0.9422
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- Recall: 0.9425
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- F1: 0.9420
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0005
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- distributed_type: multi-GPU
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.9969 | 1.0 | 125 | 0.7141 | 0.7758 | 0.7913 | 0.7716 | 0.7652 |
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| 0.7535 | 2.0 | 250 | 0.6724 | 0.8038 | 0.8426 | 0.8040 | 0.8019 |
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| 0.6749 | 3.0 | 375 | 0.4999 | 0.8428 | 0.8615 | 0.8378 | 0.8410 |
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| 0.4791 | 4.0 | 500 | 0.4593 | 0.8599 | 0.8766 | 0.8529 | 0.8562 |
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| 0.4112 | 5.0 | 625 | 0.3726 | 0.8899 | 0.8925 | 0.8852 | 0.8852 |
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| 0.3416 | 6.0 | 750 | 0.2770 | 0.9169 | 0.9137 | 0.9161 | 0.9133 |
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| 0.3195 | 7.0 | 875 | 0.3013 | 0.9139 | 0.9163 | 0.9069 | 0.9096 |
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| 0.1927 | 8.0 | 1000 | 0.2297 | 0.9369 | 0.9364 | 0.9344 | 0.9348 |
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| 0.1596 | 9.0 | 1125 | 0.2510 | 0.9329 | 0.9344 | 0.9326 | 0.9324 |
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| 0.1907 | 10.0 | 1250 | 0.2251 | 0.9439 | 0.9422 | 0.9425 | 0.9420 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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