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BilalMuftuoglu
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beit-base-patch16-224-hasta-85-fold4

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  2. model.safetensors +1 -1
  3. runs/May23_15-34-50_2bc4f829fe52/events.out.tfevents.1716478492.2bc4f829fe52.989.36 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-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: beit-base-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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+ # beit-base-patch16-224-hasta-85-fold4
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7462
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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 | 1.0761 | 0.6364 |
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+ | No log | 2.0 | 2 | 0.9258 | 0.7273 |
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+ | No log | 3.0 | 3 | 0.8310 | 0.7273 |
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+ | No log | 4.0 | 4 | 0.9402 | 0.7273 |
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+ | No log | 5.0 | 5 | 1.1381 | 0.7273 |
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+ | No log | 6.0 | 6 | 1.2812 | 0.7273 |
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+ | No log | 7.0 | 7 | 1.2679 | 0.7273 |
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+ | No log | 8.0 | 8 | 1.1704 | 0.7273 |
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+ | No log | 9.0 | 9 | 1.1909 | 0.7273 |
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+ | 0.3269 | 10.0 | 10 | 1.2981 | 0.7273 |
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+ | 0.3269 | 11.0 | 11 | 1.2565 | 0.7273 |
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+ | 0.3269 | 12.0 | 12 | 1.1475 | 0.7273 |
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+ | 0.3269 | 13.0 | 13 | 1.0585 | 0.7273 |
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+ | 0.3269 | 14.0 | 14 | 1.0294 | 0.7273 |
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+ | 0.3269 | 15.0 | 15 | 1.0649 | 0.7273 |
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+ | 0.3269 | 16.0 | 16 | 1.1712 | 0.7273 |
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+ | 0.3269 | 17.0 | 17 | 1.2090 | 0.7273 |
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+ | 0.3269 | 18.0 | 18 | 1.1579 | 0.7273 |
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+ | 0.3269 | 19.0 | 19 | 1.0943 | 0.7273 |
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+ | 0.1921 | 20.0 | 20 | 1.1877 | 0.7273 |
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+ | 0.1921 | 21.0 | 21 | 1.3909 | 0.7273 |
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+ | 0.1921 | 22.0 | 22 | 1.4301 | 0.7273 |
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+ | 0.1921 | 23.0 | 23 | 1.4210 | 0.7273 |
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+ | 0.1921 | 24.0 | 24 | 1.3994 | 0.7273 |
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+ | 0.1921 | 25.0 | 25 | 1.3649 | 0.7273 |
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+ | 0.1921 | 26.0 | 26 | 1.3244 | 0.7273 |
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+ | 0.1921 | 27.0 | 27 | 1.2861 | 0.7273 |
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+ | 0.1921 | 28.0 | 28 | 1.1634 | 0.7273 |
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+ | 0.1921 | 29.0 | 29 | 0.9854 | 0.7273 |
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+ | 0.1374 | 30.0 | 30 | 1.0608 | 0.7273 |
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+ | 0.1374 | 31.0 | 31 | 1.3092 | 0.7273 |
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+ | 0.1374 | 32.0 | 32 | 1.4679 | 0.7273 |
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+ | 0.1374 | 33.0 | 33 | 1.4397 | 0.7273 |
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+ | 0.1374 | 34.0 | 34 | 1.2949 | 0.7273 |
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+ | 0.1374 | 35.0 | 35 | 1.2340 | 0.7273 |
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+ | 0.1374 | 36.0 | 36 | 1.2524 | 0.7273 |
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+ | 0.1374 | 37.0 | 37 | 1.2108 | 0.7273 |
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+ | 0.1374 | 38.0 | 38 | 1.1878 | 0.7273 |
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+ | 0.1374 | 39.0 | 39 | 1.1400 | 0.7273 |
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+ | 0.0886 | 40.0 | 40 | 1.1186 | 0.7273 |
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+ | 0.0886 | 41.0 | 41 | 1.3145 | 0.7273 |
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+ | 0.0886 | 42.0 | 42 | 1.4749 | 0.7273 |
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+ | 0.0886 | 43.0 | 43 | 1.5773 | 0.7273 |
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+ | 0.0886 | 44.0 | 44 | 1.6792 | 0.7273 |
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+ | 0.0886 | 45.0 | 45 | 1.7716 | 0.7273 |
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+ | 0.0886 | 46.0 | 46 | 1.8943 | 0.7273 |
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+ | 0.0886 | 47.0 | 47 | 1.8541 | 0.7273 |
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+ | 0.0886 | 48.0 | 48 | 1.6656 | 0.7273 |
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+ | 0.0886 | 49.0 | 49 | 1.4897 | 0.7273 |
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+ | 0.0509 | 50.0 | 50 | 1.2921 | 0.7273 |
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+ | 0.0509 | 51.0 | 51 | 1.2021 | 0.7273 |
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+ | 0.0509 | 52.0 | 52 | 1.2643 | 0.7273 |
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+ | 0.0509 | 53.0 | 53 | 1.4622 | 0.7273 |
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+ | 0.0509 | 54.0 | 54 | 1.5043 | 0.7273 |
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+ | 0.0509 | 55.0 | 55 | 1.5063 | 0.7273 |
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+ | 0.0509 | 56.0 | 56 | 1.4604 | 0.7273 |
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+ | 0.0509 | 57.0 | 57 | 1.3414 | 0.7273 |
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+ | 0.0509 | 58.0 | 58 | 1.1789 | 0.7273 |
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+ | 0.0509 | 59.0 | 59 | 1.1715 | 0.7273 |
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+ | 0.0471 | 60.0 | 60 | 1.2550 | 0.7273 |
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+ | 0.0471 | 61.0 | 61 | 1.3513 | 0.7273 |
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+ | 0.0471 | 62.0 | 62 | 1.4922 | 0.7273 |
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+ | 0.0471 | 63.0 | 63 | 1.6911 | 0.7273 |
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+ | 0.0471 | 64.0 | 64 | 1.7747 | 0.7273 |
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+ | 0.0471 | 65.0 | 65 | 1.7659 | 0.7273 |
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+ | 0.0471 | 66.0 | 66 | 1.6730 | 0.7273 |
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+ | 0.0471 | 67.0 | 67 | 1.5296 | 0.7273 |
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+ | 0.0471 | 68.0 | 68 | 1.4973 | 0.7273 |
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+ | 0.0471 | 69.0 | 69 | 1.4650 | 0.7273 |
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+ | 0.0212 | 70.0 | 70 | 1.4970 | 0.7273 |
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+ | 0.0212 | 71.0 | 71 | 1.5022 | 0.7273 |
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+ | 0.0212 | 72.0 | 72 | 1.5275 | 0.7273 |
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+ | 0.0212 | 73.0 | 73 | 1.5780 | 0.7273 |
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+ | 0.0212 | 74.0 | 74 | 1.7149 | 0.7273 |
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+ | 0.0212 | 75.0 | 75 | 1.8056 | 0.7273 |
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+ | 0.0212 | 76.0 | 76 | 1.8394 | 0.7273 |
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+ | 0.0212 | 77.0 | 77 | 1.8526 | 0.7273 |
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+ | 0.0212 | 78.0 | 78 | 1.7944 | 0.7273 |
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+ | 0.0212 | 79.0 | 79 | 1.7440 | 0.7273 |
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+ | 0.0313 | 80.0 | 80 | 1.6994 | 0.7273 |
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+ | 0.0313 | 81.0 | 81 | 1.6076 | 0.7273 |
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+ | 0.0313 | 82.0 | 82 | 1.5753 | 0.7273 |
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+ | 0.0313 | 83.0 | 83 | 1.5831 | 0.7273 |
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+ | 0.0313 | 84.0 | 84 | 1.5471 | 0.7273 |
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+ | 0.0313 | 85.0 | 85 | 1.5600 | 0.7273 |
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+ | 0.0313 | 86.0 | 86 | 1.5832 | 0.7273 |
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+ | 0.0313 | 87.0 | 87 | 1.5819 | 0.7273 |
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+ | 0.0313 | 88.0 | 88 | 1.6053 | 0.7273 |
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+ | 0.0313 | 89.0 | 89 | 1.6329 | 0.7273 |
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+ | 0.0205 | 90.0 | 90 | 1.6751 | 0.7273 |
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+ | 0.0205 | 91.0 | 91 | 1.6957 | 0.7273 |
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+ | 0.0205 | 92.0 | 92 | 1.7326 | 0.7273 |
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+ | 0.0205 | 93.0 | 93 | 1.7475 | 0.7273 |
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+ | 0.0205 | 94.0 | 94 | 1.7503 | 0.7273 |
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+ | 0.0205 | 95.0 | 95 | 1.7443 | 0.7273 |
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+ | 0.0205 | 96.0 | 96 | 1.7483 | 0.7273 |
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+ | 0.0205 | 97.0 | 97 | 1.7523 | 0.7273 |
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+ | 0.0205 | 98.0 | 98 | 1.7516 | 0.7273 |
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+ | 0.0205 | 99.0 | 99 | 1.7483 | 0.7273 |
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+ | 0.0334 | 100.0 | 100 | 1.7462 | 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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