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BilalMuftuoglu
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deit-base-distilled-patch16-224-hasta-85-fold4

Image Classification
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  1. README.md +177 -0
  2. model.safetensors +1 -1
  3. runs/May22_16-16-24_927069b479b5/events.out.tfevents.1716394585.927069b479b5.252.42 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/deit-base-distilled-patch16-224
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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: deit-base-distilled-patch16-224-hasta-85-fold4
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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: 0.7272727272727273
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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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+ # deit-base-distilled-patch16-224-hasta-85-fold4
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+
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+ This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.3933
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+ - Accuracy: 0.7273
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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: 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: 100
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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 | 1.0 | 1 | 2.0908 | 0.0 |
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+ | No log | 2.0 | 2 | 1.8864 | 0.0 |
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+ | No log | 3.0 | 3 | 1.5313 | 0.0 |
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+ | No log | 4.0 | 4 | 1.1520 | 0.3636 |
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+ | No log | 5.0 | 5 | 0.9542 | 0.7273 |
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+ | No log | 6.0 | 6 | 1.0324 | 0.7273 |
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+ | No log | 7.0 | 7 | 1.1792 | 0.7273 |
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+ | No log | 8.0 | 8 | 1.2680 | 0.7273 |
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+ | No log | 9.0 | 9 | 1.2078 | 0.7273 |
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+ | 0.4805 | 10.0 | 10 | 1.1594 | 0.7273 |
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+ | 0.4805 | 11.0 | 11 | 1.1604 | 0.7273 |
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+ | 0.4805 | 12.0 | 12 | 1.1110 | 0.7273 |
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+ | 0.4805 | 13.0 | 13 | 1.1074 | 0.7273 |
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+ | 0.4805 | 14.0 | 14 | 1.1010 | 0.7273 |
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+ | 0.4805 | 15.0 | 15 | 1.0594 | 0.7273 |
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+ | 0.4805 | 16.0 | 16 | 1.0675 | 0.7273 |
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+ | 0.4805 | 17.0 | 17 | 1.1689 | 0.7273 |
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+ | 0.4805 | 18.0 | 18 | 1.2630 | 0.7273 |
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+ | 0.4805 | 19.0 | 19 | 1.3017 | 0.7273 |
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+ | 0.1904 | 20.0 | 20 | 1.3083 | 0.7273 |
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+ | 0.1904 | 21.0 | 21 | 1.3764 | 0.7273 |
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+ | 0.1904 | 22.0 | 22 | 1.4229 | 0.7273 |
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+ | 0.1904 | 23.0 | 23 | 1.4830 | 0.7273 |
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+ | 0.1904 | 24.0 | 24 | 1.4698 | 0.7273 |
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+ | 0.1904 | 25.0 | 25 | 1.4947 | 0.7273 |
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+ | 0.1904 | 26.0 | 26 | 1.5839 | 0.7273 |
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+ | 0.1904 | 27.0 | 27 | 1.7219 | 0.7273 |
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+ | 0.1904 | 28.0 | 28 | 1.7474 | 0.7273 |
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+ | 0.1904 | 29.0 | 29 | 1.6645 | 0.7273 |
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+ | 0.1472 | 30.0 | 30 | 1.5988 | 0.7273 |
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+ | 0.1472 | 31.0 | 31 | 1.5703 | 0.7273 |
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+ | 0.1472 | 32.0 | 32 | 1.5965 | 0.7273 |
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+ | 0.1472 | 33.0 | 33 | 1.6618 | 0.7273 |
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+ | 0.1472 | 34.0 | 34 | 1.6432 | 0.7273 |
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+ | 0.1472 | 35.0 | 35 | 1.5392 | 0.7273 |
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+ | 0.1472 | 36.0 | 36 | 1.4368 | 0.7273 |
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+ | 0.1472 | 37.0 | 37 | 1.4019 | 0.7273 |
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+ | 0.1472 | 38.0 | 38 | 1.4714 | 0.7273 |
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+ | 0.1472 | 39.0 | 39 | 1.7523 | 0.7273 |
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+ | 0.0741 | 40.0 | 40 | 1.8653 | 0.7273 |
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+ | 0.0741 | 41.0 | 41 | 1.8966 | 0.7273 |
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+ | 0.0741 | 42.0 | 42 | 1.8252 | 0.7273 |
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+ | 0.0741 | 43.0 | 43 | 1.8433 | 0.7273 |
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+ | 0.0741 | 44.0 | 44 | 1.7327 | 0.7273 |
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+ | 0.0741 | 45.0 | 45 | 1.7456 | 0.7273 |
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+ | 0.0741 | 46.0 | 46 | 1.8948 | 0.7273 |
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+ | 0.0741 | 47.0 | 47 | 1.8811 | 0.7273 |
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+ | 0.0741 | 48.0 | 48 | 1.8930 | 0.7273 |
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+ | 0.0741 | 49.0 | 49 | 1.8065 | 0.7273 |
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+ | 0.0506 | 50.0 | 50 | 1.7629 | 0.7273 |
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+ | 0.0506 | 51.0 | 51 | 1.7893 | 0.7273 |
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+ | 0.0506 | 52.0 | 52 | 1.8770 | 0.7273 |
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+ | 0.0506 | 53.0 | 53 | 1.9144 | 0.7273 |
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+ | 0.0506 | 54.0 | 54 | 2.0357 | 0.7273 |
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+ | 0.0506 | 55.0 | 55 | 2.2103 | 0.7273 |
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+ | 0.0506 | 56.0 | 56 | 2.2568 | 0.7273 |
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+ | 0.0506 | 57.0 | 57 | 2.2401 | 0.7273 |
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+ | 0.0506 | 58.0 | 58 | 2.1406 | 0.7273 |
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+ | 0.0506 | 59.0 | 59 | 2.0280 | 0.7273 |
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+ | 0.0355 | 60.0 | 60 | 1.9517 | 0.7273 |
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+ | 0.0355 | 61.0 | 61 | 1.8787 | 0.7273 |
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+ | 0.0355 | 62.0 | 62 | 1.8958 | 0.7273 |
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+ | 0.0355 | 63.0 | 63 | 1.9893 | 0.7273 |
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+ | 0.0355 | 64.0 | 64 | 2.1195 | 0.7273 |
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+ | 0.0355 | 65.0 | 65 | 2.2715 | 0.7273 |
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+ | 0.0355 | 66.0 | 66 | 2.3640 | 0.7273 |
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+ | 0.0355 | 67.0 | 67 | 2.4391 | 0.7273 |
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+ | 0.0355 | 68.0 | 68 | 2.4633 | 0.7273 |
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+ | 0.0355 | 69.0 | 69 | 2.4489 | 0.7273 |
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+ | 0.021 | 70.0 | 70 | 2.4177 | 0.7273 |
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+ | 0.021 | 71.0 | 71 | 2.3674 | 0.7273 |
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+ | 0.021 | 72.0 | 72 | 2.3065 | 0.7273 |
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+ | 0.021 | 73.0 | 73 | 2.2978 | 0.7273 |
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+ | 0.021 | 74.0 | 74 | 2.3590 | 0.7273 |
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+ | 0.021 | 75.0 | 75 | 2.4277 | 0.7273 |
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+ | 0.021 | 76.0 | 76 | 2.5220 | 0.7273 |
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+ | 0.021 | 77.0 | 77 | 2.6248 | 0.7273 |
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+ | 0.021 | 78.0 | 78 | 2.6925 | 0.7273 |
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+ | 0.021 | 79.0 | 79 | 2.7284 | 0.7273 |
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+ | 0.0346 | 80.0 | 80 | 2.7409 | 0.7273 |
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+ | 0.0346 | 81.0 | 81 | 2.7218 | 0.7273 |
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+ | 0.0346 | 82.0 | 82 | 2.6717 | 0.7273 |
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+ | 0.0346 | 83.0 | 83 | 2.6142 | 0.7273 |
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+ | 0.0346 | 84.0 | 84 | 2.5196 | 0.7273 |
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+ | 0.0346 | 85.0 | 85 | 2.4438 | 0.7273 |
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+ | 0.0346 | 86.0 | 86 | 2.3812 | 0.7273 |
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+ | 0.0346 | 87.0 | 87 | 2.3026 | 0.7273 |
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+ | 0.0346 | 88.0 | 88 | 2.2691 | 0.7273 |
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+ | 0.0346 | 89.0 | 89 | 2.2665 | 0.7273 |
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+ | 0.0219 | 90.0 | 90 | 2.2659 | 0.7273 |
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+ | 0.0219 | 91.0 | 91 | 2.2735 | 0.7273 |
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+ | 0.0219 | 92.0 | 92 | 2.3000 | 0.7273 |
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+ | 0.0219 | 93.0 | 93 | 2.3136 | 0.7273 |
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+ | 0.0219 | 94.0 | 94 | 2.3247 | 0.7273 |
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+ | 0.0219 | 95.0 | 95 | 2.3388 | 0.7273 |
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+ | 0.0219 | 96.0 | 96 | 2.3597 | 0.7273 |
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+ | 0.0219 | 97.0 | 97 | 2.3746 | 0.7273 |
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+ | 0.0219 | 98.0 | 98 | 2.3864 | 0.7273 |
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+ | 0.0219 | 99.0 | 99 | 2.3913 | 0.7273 |
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+ | 0.0286 | 100.0 | 100 | 2.3933 | 0.7273 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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