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End of training
Browse files- README.md +72 -0
- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
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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: Train-Test-Augmentation-swinv2-base
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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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# Train-Test-Augmentation-swinv2-base
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This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7329
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- Accuracy: 0.8206
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 256
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.5364 | 0.98 | 23 | 0.8286 | 0.7257 |
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| 0.4948 | 1.97 | 46 | 0.6373 | 0.7958 |
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| 0.2036 | 2.99 | 70 | 0.5860 | 0.8234 |
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| 0.1158 | 3.98 | 93 | 0.6284 | 0.8151 |
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| 0.0656 | 4.96 | 116 | 0.6982 | 0.8129 |
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| 0.0568 | 5.99 | 140 | 0.7678 | 0.8217 |
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| 0.0332 | 6.97 | 163 | 0.7208 | 0.8206 |
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| 0.0279 | 8.0 | 187 | 0.7053 | 0.8217 |
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| 0.0169 | 8.98 | 210 | 0.7489 | 0.8256 |
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| 0.0125 | 9.84 | 230 | 0.7329 | 0.8206 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.1.2
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- Datasets 2.19.1
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- Tokenizers 0.15.2
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model.safetensors
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