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--- |
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license: apache-2.0 |
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base_model: facebook/convnextv2-base-1k-224 |
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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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model-index: |
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- name: convnextv2-base-1k-224-for-pre_evaluation |
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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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# convnextv2-base-1k-224-for-pre_evaluation |
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This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3599 |
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- Accuracy: 0.4190 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.6 | 1.0 | 16 | 1.5316 | 0.2961 | |
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| 1.5084 | 2.0 | 32 | 1.5061 | 0.2849 | |
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| 1.5134 | 3.0 | 48 | 1.4968 | 0.3240 | |
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| 1.4663 | 4.0 | 64 | 1.4607 | 0.3352 | |
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| 1.4046 | 5.0 | 80 | 1.4509 | 0.3268 | |
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| 1.4085 | 6.0 | 96 | 1.4423 | 0.3883 | |
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| 1.3443 | 7.0 | 112 | 1.4005 | 0.4022 | |
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| 1.3025 | 8.0 | 128 | 1.3599 | 0.4190 | |
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| 1.2627 | 9.0 | 144 | 1.3638 | 0.3911 | |
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| 1.2099 | 10.0 | 160 | 1.4058 | 0.3492 | |
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| 1.2086 | 11.0 | 176 | 1.4431 | 0.3408 | |
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| 1.1393 | 12.0 | 192 | 1.4143 | 0.3492 | |
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| 1.1039 | 13.0 | 208 | 1.4305 | 0.3883 | |
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| 1.0551 | 14.0 | 224 | 1.5203 | 0.3520 | |
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| 1.0368 | 15.0 | 240 | 1.5117 | 0.3324 | |
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| 0.9753 | 16.0 | 256 | 1.4545 | 0.3771 | |
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| 0.938 | 17.0 | 272 | 1.5396 | 0.3352 | |
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| 0.899 | 18.0 | 288 | 1.5770 | 0.3408 | |
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| 0.8629 | 19.0 | 304 | 1.7106 | 0.3128 | |
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| 0.8674 | 20.0 | 320 | 1.5864 | 0.3352 | |
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| 0.7789 | 21.0 | 336 | 1.6129 | 0.3408 | |
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| 0.7426 | 22.0 | 352 | 1.6353 | 0.3603 | |
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| 0.7677 | 23.0 | 368 | 1.6793 | 0.3464 | |
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| 0.7172 | 24.0 | 384 | 1.6759 | 0.3575 | |
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| 0.6809 | 25.0 | 400 | 1.7013 | 0.3659 | |
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| 0.6619 | 26.0 | 416 | 1.7108 | 0.3631 | |
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| 0.6656 | 27.0 | 432 | 1.7327 | 0.3715 | |
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| 0.6258 | 28.0 | 448 | 1.7378 | 0.3547 | |
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| 0.6173 | 29.0 | 464 | 1.7461 | 0.3603 | |
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| 0.6214 | 30.0 | 480 | 1.7475 | 0.3520 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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