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/convnext-base-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-convnext-base-384-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-convnext-base-384-finetuned-spiderTraining20-500
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This model is a fine-tuned version of [facebook/convnext-base-384](https://huggingface.co/facebook/convnext-base-384) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1900
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- Accuracy: 0.9510
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- Precision: 0.9493
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- Recall: 0.9488
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- F1: 0.9482
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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: 25
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- eval_batch_size: 25
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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: 100
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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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| 0.8521 | 1.0 | 80 | 0.6379 | 0.7838 | 0.8075 | 0.7774 | 0.7542 |
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| 0.5214 | 2.0 | 160 | 0.3445 | 0.8909 | 0.8935 | 0.8833 | 0.8847 |
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| 0.4013 | 3.0 | 240 | 0.2821 | 0.9119 | 0.9205 | 0.9048 | 0.9091 |
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| 0.3152 | 4.0 | 320 | 0.2633 | 0.9249 | 0.9264 | 0.9234 | 0.9225 |
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| 0.2552 | 5.0 | 400 | 0.2837 | 0.9229 | 0.9246 | 0.9179 | 0.9194 |
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| 0.236 | 6.0 | 480 | 0.2367 | 0.9329 | 0.9311 | 0.9309 | 0.9301 |
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| 0.2178 | 7.0 | 560 | 0.2161 | 0.9389 | 0.9384 | 0.9354 | 0.9360 |
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| 0.1712 | 8.0 | 640 | 0.1985 | 0.9459 | 0.9461 | 0.9434 | 0.9439 |
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| 0.1607 | 9.0 | 720 | 0.2024 | 0.9489 | 0.9463 | 0.9473 | 0.9454 |
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| 0.1592 | 10.0 | 800 | 0.1900 | 0.9510 | 0.9493 | 0.9488 | 0.9482 |
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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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