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BilalMuftuoglu
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deit-base-distilled-patch16-224-75-fold2

Image Classification
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  2. model.safetensors +1 -1
  3. runs/May22_00-42-41_804716d6a90a/events.out.tfevents.1716338562.804716d6a90a.958.22 +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-patch16-224-75-fold2
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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: 0.9302325581395349
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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-patch16-224-75-fold2
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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: 0.2482
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+ - Accuracy: 0.9302
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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 | 2 | 0.8815 | 0.4419 |
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+ | No log | 2.0 | 4 | 0.6436 | 0.6977 |
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+ | No log | 3.0 | 6 | 0.8488 | 0.6977 |
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+ | No log | 4.0 | 8 | 0.8219 | 0.6977 |
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+ | 0.6918 | 5.0 | 10 | 0.5491 | 0.6977 |
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+ | 0.6918 | 6.0 | 12 | 0.4603 | 0.7209 |
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+ | 0.6918 | 7.0 | 14 | 0.5602 | 0.7442 |
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+ | 0.6918 | 8.0 | 16 | 0.5694 | 0.7442 |
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+ | 0.6918 | 9.0 | 18 | 0.4430 | 0.8140 |
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+ | 0.3867 | 10.0 | 20 | 0.3880 | 0.8605 |
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+ | 0.3867 | 11.0 | 22 | 0.5069 | 0.8140 |
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+ | 0.3867 | 12.0 | 24 | 0.3739 | 0.8605 |
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+ | 0.3867 | 13.0 | 26 | 0.2981 | 0.8837 |
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+ | 0.3867 | 14.0 | 28 | 0.3170 | 0.8837 |
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+ | 0.2722 | 15.0 | 30 | 0.2511 | 0.8837 |
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+ | 0.2722 | 16.0 | 32 | 0.2408 | 0.8837 |
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+ | 0.2722 | 17.0 | 34 | 0.3751 | 0.8605 |
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+ | 0.2722 | 18.0 | 36 | 0.3081 | 0.8605 |
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+ | 0.2722 | 19.0 | 38 | 0.2489 | 0.8837 |
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+ | 0.209 | 20.0 | 40 | 0.2802 | 0.8837 |
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+ | 0.209 | 21.0 | 42 | 0.2625 | 0.9302 |
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+ | 0.209 | 22.0 | 44 | 0.2595 | 0.9302 |
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+ | 0.209 | 23.0 | 46 | 0.5048 | 0.8372 |
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+ | 0.209 | 24.0 | 48 | 0.2880 | 0.8605 |
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+ | 0.2027 | 25.0 | 50 | 0.2860 | 0.8372 |
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+ | 0.2027 | 26.0 | 52 | 0.4067 | 0.8372 |
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+ | 0.2027 | 27.0 | 54 | 0.2462 | 0.9070 |
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+ | 0.2027 | 28.0 | 56 | 0.2753 | 0.9070 |
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+ | 0.2027 | 29.0 | 58 | 0.3699 | 0.8140 |
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+ | 0.1426 | 30.0 | 60 | 0.4983 | 0.8372 |
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+ | 0.1426 | 31.0 | 62 | 0.3140 | 0.8605 |
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+ | 0.1426 | 32.0 | 64 | 0.3470 | 0.8372 |
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+ | 0.1426 | 33.0 | 66 | 0.4443 | 0.8372 |
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+ | 0.1426 | 34.0 | 68 | 0.2583 | 0.8837 |
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+ | 0.1385 | 35.0 | 70 | 0.2239 | 0.9302 |
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+ | 0.1385 | 36.0 | 72 | 0.2708 | 0.9070 |
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+ | 0.1385 | 37.0 | 74 | 0.2660 | 0.9070 |
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+ | 0.1385 | 38.0 | 76 | 0.2754 | 0.9070 |
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+ | 0.1385 | 39.0 | 78 | 0.4246 | 0.8605 |
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+ | 0.1202 | 40.0 | 80 | 0.2779 | 0.9070 |
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+ | 0.1202 | 41.0 | 82 | 0.2726 | 0.8837 |
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+ | 0.1202 | 42.0 | 84 | 0.2536 | 0.9070 |
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+ | 0.1202 | 43.0 | 86 | 0.2667 | 0.9302 |
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+ | 0.1202 | 44.0 | 88 | 0.4191 | 0.8837 |
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+ | 0.1211 | 45.0 | 90 | 0.3213 | 0.9302 |
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+ | 0.1211 | 46.0 | 92 | 0.2290 | 0.9070 |
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+ | 0.1211 | 47.0 | 94 | 0.3043 | 0.8837 |
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+ | 0.1211 | 48.0 | 96 | 0.1906 | 0.9302 |
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+ | 0.1211 | 49.0 | 98 | 0.3201 | 0.8605 |
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+ | 0.1067 | 50.0 | 100 | 0.3062 | 0.8837 |
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+ | 0.1067 | 51.0 | 102 | 0.2047 | 0.9302 |
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+ | 0.1067 | 52.0 | 104 | 0.2116 | 0.9070 |
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+ | 0.1067 | 53.0 | 106 | 0.2113 | 0.9302 |
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+ | 0.1067 | 54.0 | 108 | 0.2340 | 0.9302 |
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+ | 0.0826 | 55.0 | 110 | 0.2328 | 0.9302 |
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+ | 0.0826 | 56.0 | 112 | 0.2824 | 0.8837 |
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+ | 0.0826 | 57.0 | 114 | 0.2921 | 0.8837 |
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+ | 0.0826 | 58.0 | 116 | 0.2608 | 0.9302 |
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+ | 0.0826 | 59.0 | 118 | 0.2650 | 0.9302 |
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+ | 0.0894 | 60.0 | 120 | 0.2878 | 0.9070 |
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+ | 0.0894 | 61.0 | 122 | 0.2935 | 0.9070 |
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+ | 0.0894 | 62.0 | 124 | 0.2656 | 0.9302 |
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+ | 0.0894 | 63.0 | 126 | 0.3438 | 0.9070 |
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+ | 0.0894 | 64.0 | 128 | 0.2840 | 0.9302 |
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+ | 0.0964 | 65.0 | 130 | 0.2711 | 0.9070 |
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+ | 0.0964 | 66.0 | 132 | 0.2888 | 0.9070 |
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+ | 0.0964 | 67.0 | 134 | 0.2723 | 0.9070 |
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+ | 0.0964 | 68.0 | 136 | 0.2563 | 0.8837 |
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+ | 0.0964 | 69.0 | 138 | 0.2336 | 0.9302 |
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+ | 0.0711 | 70.0 | 140 | 0.2386 | 0.9302 |
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+ | 0.0711 | 71.0 | 142 | 0.2482 | 0.9070 |
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+ | 0.0711 | 72.0 | 144 | 0.2821 | 0.9070 |
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+ | 0.0711 | 73.0 | 146 | 0.2941 | 0.8837 |
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+ | 0.0711 | 74.0 | 148 | 0.2564 | 0.9070 |
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+ | 0.0824 | 75.0 | 150 | 0.2509 | 0.9302 |
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+ | 0.0824 | 76.0 | 152 | 0.2544 | 0.9302 |
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+ | 0.0824 | 77.0 | 154 | 0.2474 | 0.9302 |
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+ | 0.0824 | 78.0 | 156 | 0.2375 | 0.9302 |
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+ | 0.0824 | 79.0 | 158 | 0.2389 | 0.9302 |
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+ | 0.0691 | 80.0 | 160 | 0.2371 | 0.9302 |
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+ | 0.0691 | 81.0 | 162 | 0.2393 | 0.9302 |
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+ | 0.0691 | 82.0 | 164 | 0.2523 | 0.9070 |
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+ | 0.0691 | 83.0 | 166 | 0.2677 | 0.8837 |
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+ | 0.0691 | 84.0 | 168 | 0.2945 | 0.8837 |
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+ | 0.0638 | 85.0 | 170 | 0.3245 | 0.8605 |
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+ | 0.0638 | 86.0 | 172 | 0.2960 | 0.8837 |
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+ | 0.0638 | 87.0 | 174 | 0.2658 | 0.9302 |
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+ | 0.0638 | 88.0 | 176 | 0.2614 | 0.9302 |
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+ | 0.0638 | 89.0 | 178 | 0.2613 | 0.9302 |
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+ | 0.0705 | 90.0 | 180 | 0.2549 | 0.9302 |
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+ | 0.0705 | 91.0 | 182 | 0.2510 | 0.9302 |
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+ | 0.0705 | 92.0 | 184 | 0.2514 | 0.9302 |
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+ | 0.0705 | 93.0 | 186 | 0.2522 | 0.9302 |
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+ | 0.0705 | 94.0 | 188 | 0.2504 | 0.9070 |
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+ | 0.0666 | 95.0 | 190 | 0.2459 | 0.9302 |
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+ | 0.0666 | 96.0 | 192 | 0.2424 | 0.9302 |
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+ | 0.0666 | 97.0 | 194 | 0.2428 | 0.9302 |
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+ | 0.0666 | 98.0 | 196 | 0.2451 | 0.9302 |
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+ | 0.0666 | 99.0 | 198 | 0.2471 | 0.9302 |
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+ | 0.0566 | 100.0 | 200 | 0.2482 | 0.9302 |
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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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