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--- |
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license: apache-2.0 |
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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: models |
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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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# models |
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This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4704 |
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- Accuracy: 0.8182 |
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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: 20 |
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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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| 1.4144 | 0.99 | 20 | 0.9938 | 0.7 | |
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| 0.7896 | 1.98 | 40 | 0.7022 | 0.7152 | |
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| 0.6191 | 2.96 | 60 | 0.6079 | 0.7636 | |
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| 0.6114 | 4.0 | 81 | 0.5554 | 0.7939 | |
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| 0.5365 | 4.99 | 101 | 0.5233 | 0.8152 | |
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| 0.4989 | 5.98 | 121 | 0.4934 | 0.8303 | |
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| 0.5111 | 6.96 | 141 | 0.5181 | 0.8 | |
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| 0.476 | 8.0 | 162 | 0.4844 | 0.8182 | |
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| 0.4655 | 8.99 | 182 | 0.4870 | 0.8152 | |
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| 0.4335 | 9.98 | 202 | 0.4802 | 0.8242 | |
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| 0.44 | 10.96 | 222 | 0.4776 | 0.8182 | |
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| 0.3989 | 12.0 | 243 | 0.4804 | 0.8182 | |
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| 0.4007 | 12.99 | 263 | 0.4768 | 0.8242 | |
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| 0.3987 | 13.98 | 283 | 0.4610 | 0.8303 | |
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| 0.3922 | 14.96 | 303 | 0.4578 | 0.8212 | |
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| 0.3924 | 16.0 | 324 | 0.4804 | 0.8182 | |
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| 0.3995 | 16.99 | 344 | 0.4736 | 0.8121 | |
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| 0.3623 | 17.98 | 364 | 0.4715 | 0.8121 | |
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| 0.3621 | 18.96 | 384 | 0.4671 | 0.8212 | |
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| 0.3629 | 19.75 | 400 | 0.4704 | 0.8182 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
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