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BilalMuftuoglu
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deit-base-distilled-patch16-224-85-fold1

Image Classification
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  1. README.md +177 -0
  2. model.safetensors +1 -1
  3. runs/May22_01-59-06_804716d6a90a/events.out.tfevents.1716343147.804716d6a90a.958.30 +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-patch16-224-85-fold1
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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: 0.9318181818181818
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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-patch16-224-85-fold1
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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: 0.2096
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+ - Accuracy: 0.9318
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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 | 1.1776 | 0.25 |
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+ | No log | 2.0 | 4 | 0.8165 | 0.3182 |
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+ | No log | 3.0 | 6 | 0.7525 | 0.7045 |
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+ | No log | 4.0 | 8 | 0.8074 | 0.7045 |
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+ | 0.7495 | 5.0 | 10 | 0.6842 | 0.7045 |
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+ | 0.7495 | 6.0 | 12 | 0.5606 | 0.6818 |
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+ | 0.7495 | 7.0 | 14 | 0.5377 | 0.6818 |
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+ | 0.7495 | 8.0 | 16 | 0.5761 | 0.7045 |
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+ | 0.7495 | 9.0 | 18 | 0.5866 | 0.7045 |
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+ | 0.4611 | 10.0 | 20 | 0.4894 | 0.7273 |
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+ | 0.4611 | 11.0 | 22 | 0.6216 | 0.7273 |
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+ | 0.4611 | 12.0 | 24 | 0.6272 | 0.7273 |
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+ | 0.4611 | 13.0 | 26 | 0.4476 | 0.7727 |
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+ | 0.4611 | 14.0 | 28 | 0.4451 | 0.75 |
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+ | 0.3766 | 15.0 | 30 | 0.4370 | 0.7727 |
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+ | 0.3766 | 16.0 | 32 | 0.4937 | 0.75 |
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+ | 0.3766 | 17.0 | 34 | 0.4977 | 0.7955 |
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+ | 0.3766 | 18.0 | 36 | 0.4551 | 0.8409 |
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+ | 0.3766 | 19.0 | 38 | 0.3776 | 0.7727 |
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+ | 0.3147 | 20.0 | 40 | 0.3347 | 0.8409 |
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+ | 0.3147 | 21.0 | 42 | 0.5178 | 0.7727 |
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+ | 0.3147 | 22.0 | 44 | 0.3430 | 0.8409 |
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+ | 0.3147 | 23.0 | 46 | 0.3091 | 0.8409 |
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+ | 0.3147 | 24.0 | 48 | 0.3995 | 0.8864 |
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+ | 0.2176 | 25.0 | 50 | 0.2971 | 0.8409 |
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+ | 0.2176 | 26.0 | 52 | 0.3137 | 0.8864 |
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+ | 0.2176 | 27.0 | 54 | 0.2694 | 0.8864 |
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+ | 0.2176 | 28.0 | 56 | 0.2589 | 0.8864 |
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+ | 0.2176 | 29.0 | 58 | 0.3612 | 0.8636 |
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+ | 0.1855 | 30.0 | 60 | 0.3406 | 0.8636 |
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+ | 0.1855 | 31.0 | 62 | 0.4738 | 0.8864 |
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+ | 0.1855 | 32.0 | 64 | 0.7612 | 0.7955 |
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+ | 0.1855 | 33.0 | 66 | 0.5307 | 0.8864 |
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+ | 0.1855 | 34.0 | 68 | 0.3346 | 0.8636 |
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+ | 0.2006 | 35.0 | 70 | 0.3562 | 0.8409 |
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+ | 0.2006 | 36.0 | 72 | 0.5255 | 0.8409 |
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+ | 0.2006 | 37.0 | 74 | 0.3795 | 0.8409 |
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+ | 0.2006 | 38.0 | 76 | 0.2924 | 0.9091 |
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+ | 0.2006 | 39.0 | 78 | 0.2921 | 0.8864 |
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+ | 0.161 | 40.0 | 80 | 0.3895 | 0.8409 |
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+ | 0.161 | 41.0 | 82 | 0.3421 | 0.8182 |
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+ | 0.161 | 42.0 | 84 | 0.2674 | 0.8864 |
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+ | 0.161 | 43.0 | 86 | 0.2586 | 0.8864 |
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+ | 0.161 | 44.0 | 88 | 0.4520 | 0.8409 |
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+ | 0.1588 | 45.0 | 90 | 0.4300 | 0.8409 |
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+ | 0.1588 | 46.0 | 92 | 0.2424 | 0.9318 |
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+ | 0.1588 | 47.0 | 94 | 0.2645 | 0.9318 |
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+ | 0.1588 | 48.0 | 96 | 0.2531 | 0.8864 |
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+ | 0.1588 | 49.0 | 98 | 0.2614 | 0.8864 |
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+ | 0.1103 | 50.0 | 100 | 0.3024 | 0.8864 |
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+ | 0.1103 | 51.0 | 102 | 0.2797 | 0.9091 |
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+ | 0.1103 | 52.0 | 104 | 0.2307 | 0.9545 |
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+ | 0.1103 | 53.0 | 106 | 0.2635 | 0.9091 |
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+ | 0.1103 | 54.0 | 108 | 0.5111 | 0.8409 |
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+ | 0.1201 | 55.0 | 110 | 0.5371 | 0.8409 |
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+ | 0.1201 | 56.0 | 112 | 0.2940 | 0.8864 |
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+ | 0.1201 | 57.0 | 114 | 0.3015 | 0.9091 |
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+ | 0.1201 | 58.0 | 116 | 0.2631 | 0.8864 |
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+ | 0.1201 | 59.0 | 118 | 0.2830 | 0.8864 |
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+ | 0.1037 | 60.0 | 120 | 0.3202 | 0.8636 |
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+ | 0.1037 | 61.0 | 122 | 0.3526 | 0.8636 |
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+ | 0.1037 | 62.0 | 124 | 0.3975 | 0.8409 |
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+ | 0.1037 | 63.0 | 126 | 0.4785 | 0.8409 |
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+ | 0.1037 | 64.0 | 128 | 0.4306 | 0.8636 |
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+ | 0.1 | 65.0 | 130 | 0.3230 | 0.8636 |
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+ | 0.1 | 66.0 | 132 | 0.3007 | 0.8864 |
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+ | 0.1 | 67.0 | 134 | 0.2669 | 0.8864 |
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+ | 0.1 | 68.0 | 136 | 0.2335 | 0.8864 |
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+ | 0.1 | 69.0 | 138 | 0.1845 | 0.8864 |
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+ | 0.0984 | 70.0 | 140 | 0.2261 | 0.8864 |
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+ | 0.0984 | 71.0 | 142 | 0.3015 | 0.8864 |
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+ | 0.0984 | 72.0 | 144 | 0.3138 | 0.8864 |
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+ | 0.0984 | 73.0 | 146 | 0.2444 | 0.8864 |
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+ | 0.0984 | 74.0 | 148 | 0.2060 | 0.9091 |
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+ | 0.0826 | 75.0 | 150 | 0.2024 | 0.9318 |
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+ | 0.0826 | 76.0 | 152 | 0.2503 | 0.8864 |
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+ | 0.0826 | 77.0 | 154 | 0.2499 | 0.8864 |
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+ | 0.0826 | 78.0 | 156 | 0.2099 | 0.9091 |
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+ | 0.0826 | 79.0 | 158 | 0.2240 | 0.9091 |
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+ | 0.0701 | 80.0 | 160 | 0.2228 | 0.9091 |
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+ | 0.0701 | 81.0 | 162 | 0.2337 | 0.9091 |
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+ | 0.0701 | 82.0 | 164 | 0.2113 | 0.9318 |
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+ | 0.0701 | 83.0 | 166 | 0.1977 | 0.9091 |
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+ | 0.0701 | 84.0 | 168 | 0.2021 | 0.9091 |
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+ | 0.0846 | 85.0 | 170 | 0.2330 | 0.9318 |
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+ | 0.0846 | 86.0 | 172 | 0.2333 | 0.9318 |
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+ | 0.0846 | 87.0 | 174 | 0.2130 | 0.9318 |
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+ | 0.0846 | 88.0 | 176 | 0.2090 | 0.9091 |
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+ | 0.0846 | 89.0 | 178 | 0.2114 | 0.9091 |
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+ | 0.0932 | 90.0 | 180 | 0.2061 | 0.9091 |
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+ | 0.0932 | 91.0 | 182 | 0.2174 | 0.9091 |
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+ | 0.0932 | 92.0 | 184 | 0.2429 | 0.9091 |
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+ | 0.0932 | 93.0 | 186 | 0.2459 | 0.9091 |
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+ | 0.0932 | 94.0 | 188 | 0.2293 | 0.9318 |
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+ | 0.0742 | 95.0 | 190 | 0.2127 | 0.9318 |
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+ | 0.0742 | 96.0 | 192 | 0.2014 | 0.9091 |
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+ | 0.0742 | 97.0 | 194 | 0.2015 | 0.9091 |
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+ | 0.0742 | 98.0 | 196 | 0.2063 | 0.9318 |
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+ | 0.0742 | 99.0 | 198 | 0.2088 | 0.9318 |
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+ | 0.0701 | 100.0 | 200 | 0.2096 | 0.9318 |
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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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