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Melo1512
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vit-msn-small-beta-fia-manually-enhanced_test_1

Image Classification
Transformers
TensorBoard
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vit_msn
Generated from Trainer
Eval Results
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  3. runs/Jan24_17-30-03_ef765fa7224c/events.out.tfevents.1737739812.ef765fa7224c.194.0 +2 -2
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: facebook/vit-msn-small
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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: vit-msn-small-beta-fia-manually-enhanced_test_1
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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: test
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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: 0.676056338028169
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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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+ # vit-msn-small-beta-fia-manually-enhanced_test_1
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+
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+ This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7447
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+ - Accuracy: 0.6761
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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: 1e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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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: 0.2
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+ - num_epochs: 50
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+ - label_smoothing_factor: 0.1
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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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+ | No log | 0.5714 | 1 | 0.9554 | 0.3732 |
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+ | No log | 1.7143 | 3 | 0.9304 | 0.5211 |
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+ | No log | 2.8571 | 5 | 0.8979 | 0.6338 |
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+ | No log | 4.0 | 7 | 0.8770 | 0.6479 |
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+ | No log | 4.5714 | 8 | 0.8595 | 0.6408 |
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+ | 0.877 | 5.7143 | 10 | 0.8456 | 0.5634 |
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+ | 0.877 | 6.8571 | 12 | 0.8825 | 0.4859 |
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+ | 0.877 | 8.0 | 14 | 0.8294 | 0.5563 |
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+ | 0.877 | 8.5714 | 15 | 0.7883 | 0.6197 |
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+ | 0.877 | 9.7143 | 17 | 0.7541 | 0.6549 |
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+ | 0.877 | 10.8571 | 19 | 0.7689 | 0.6690 |
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+ | 0.7053 | 12.0 | 21 | 0.7652 | 0.6620 |
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+ | 0.7053 | 12.5714 | 22 | 0.7496 | 0.6690 |
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+ | 0.7053 | 13.7143 | 24 | 0.7139 | 0.7183 |
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+ | 0.7053 | 14.8571 | 26 | 0.7014 | 0.7465 |
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+ | 0.7053 | 16.0 | 28 | 0.7290 | 0.7183 |
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+ | 0.7053 | 16.5714 | 29 | 0.7431 | 0.6901 |
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+ | 0.6176 | 17.7143 | 31 | 0.7498 | 0.6690 |
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+ | 0.6176 | 18.8571 | 33 | 0.7439 | 0.6761 |
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+ | 0.6176 | 20.0 | 35 | 0.7347 | 0.6972 |
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+ | 0.6176 | 20.5714 | 36 | 0.7377 | 0.6901 |
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+ | 0.6176 | 21.7143 | 38 | 0.7227 | 0.6901 |
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+ | 0.6053 | 22.8571 | 40 | 0.7228 | 0.7042 |
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+ | 0.6053 | 24.0 | 42 | 0.7282 | 0.6901 |
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+ | 0.6053 | 24.5714 | 43 | 0.7363 | 0.6761 |
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+ | 0.6053 | 25.7143 | 45 | 0.7431 | 0.6831 |
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+ | 0.6053 | 26.8571 | 47 | 0.7450 | 0.6831 |
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+ | 0.6053 | 28.0 | 49 | 0.7455 | 0.6761 |
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+ | 0.5926 | 28.5714 | 50 | 0.7447 | 0.6761 |
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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 3.2.0
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+ - Tokenizers 0.19.1
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