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--- |
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license: apache-2.0 |
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base_model: google/bit-50 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: bit-50 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.085 |
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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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# bit-50 |
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This model is a fine-tuned version of [google/bit-50](https://huggingface.co/google/bit-50) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 7122385408.0 |
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- Accuracy: 0.085 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 8 |
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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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| 5528748032.0 | 1.0 | 50 | 7122386944.0 | 0.085 | |
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| 5155133849.6 | 2.0 | 100 | 7122386944.0 | 0.085 | |
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| 5068722995.2 | 3.0 | 150 | 7122386944.0 | 0.085 | |
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| 5613660569.6 | 4.0 | 200 | 7122385408.0 | 0.085 | |
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| 7499937382.4 | 5.0 | 250 | 7122385408.0 | 0.085 | |
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| 5806654259.2 | 6.0 | 300 | 7122385408.0 | 0.085 | |
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| 5483250483.2 | 7.0 | 350 | 7122385408.0 | 0.085 | |
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| 6852667392.0 | 8.0 | 400 | 7122385408.0 | 0.085 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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