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raffaelsiregar
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dog-breeds-classification

Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +65 -0
  2. config.json +170 -0
  3. model.safetensors +3 -0
  4. runs/Oct01_10-58-55_f3bbca751707/events.out.tfevents.1727780338.f3bbca751707.1737.0 +3 -0
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  6. runs/Oct01_11-01-15_f3bbca751707/events.out.tfevents.1727783289.f3bbca751707.2601.1 +3 -0
  7. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224
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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: results
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+ results: []
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+ ---
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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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+
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+ # results
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0763
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+ - Accuracy: 0.9743
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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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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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4379 | 1.0 | 249 | 0.2430 | 0.93 |
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+ | 0.1998 | 2.0 | 498 | 0.1380 | 0.9514 |
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+ | 0.0739 | 3.0 | 747 | 0.1008 | 0.9614 |
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+ | 0.0135 | 4.0 | 996 | 0.0834 | 0.9671 |
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+ | 0.0036 | 5.0 | 1245 | 0.0763 | 0.9743 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.19.1
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