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

Image Classification
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  1. README.md +177 -0
  2. model.safetensors +1 -1
  3. runs/May22_15-22-47_927069b479b5/events.out.tfevents.1716391368.927069b479b5.252.28 +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-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: 0.9166666666666666
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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-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: 0.2973
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+ - Accuracy: 0.9167
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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 | 0.8721 | 0.5833 |
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+ | No log | 2.0 | 2 | 0.7324 | 0.8333 |
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+ | No log | 3.0 | 3 | 0.5330 | 0.9167 |
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+ | No log | 4.0 | 4 | 0.4022 | 0.9167 |
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+ | No log | 5.0 | 5 | 0.3794 | 0.9167 |
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+ | No log | 6.0 | 6 | 0.3910 | 0.9167 |
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+ | No log | 7.0 | 7 | 0.3832 | 0.9167 |
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+ | No log | 8.0 | 8 | 0.3524 | 0.9167 |
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+ | No log | 9.0 | 9 | 0.4280 | 0.9167 |
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+ | 0.3237 | 10.0 | 10 | 0.5286 | 0.8333 |
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+ | 0.3237 | 11.0 | 11 | 0.4004 | 0.9167 |
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+ | 0.3237 | 12.0 | 12 | 0.3327 | 0.9167 |
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+ | 0.3237 | 13.0 | 13 | 0.3136 | 0.9167 |
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+ | 0.3237 | 14.0 | 14 | 0.2844 | 0.9167 |
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+ | 0.3237 | 15.0 | 15 | 0.2493 | 0.9167 |
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+ | 0.3237 | 16.0 | 16 | 0.2190 | 0.9167 |
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+ | 0.3237 | 17.0 | 17 | 0.1925 | 0.9167 |
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+ | 0.3237 | 18.0 | 18 | 0.1722 | 0.9167 |
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+ | 0.3237 | 19.0 | 19 | 0.1387 | 0.9167 |
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+ | 0.142 | 20.0 | 20 | 0.1259 | 0.9167 |
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+ | 0.142 | 21.0 | 21 | 0.1443 | 0.9167 |
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+ | 0.142 | 22.0 | 22 | 0.1372 | 0.9167 |
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+ | 0.142 | 23.0 | 23 | 0.1043 | 0.9167 |
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+ | 0.142 | 24.0 | 24 | 0.1022 | 0.9167 |
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+ | 0.142 | 25.0 | 25 | 0.1327 | 0.9167 |
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+ | 0.142 | 26.0 | 26 | 0.2213 | 0.9167 |
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+ | 0.142 | 27.0 | 27 | 0.2587 | 0.9167 |
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+ | 0.142 | 28.0 | 28 | 0.2411 | 0.9167 |
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+ | 0.142 | 29.0 | 29 | 0.1915 | 0.9167 |
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+ | 0.0723 | 30.0 | 30 | 0.1418 | 0.9167 |
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+ | 0.0723 | 31.0 | 31 | 0.1369 | 0.9167 |
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+ | 0.0723 | 32.0 | 32 | 0.1749 | 0.9167 |
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+ | 0.0723 | 33.0 | 33 | 0.2607 | 0.9167 |
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+ | 0.0723 | 34.0 | 34 | 0.3049 | 0.9167 |
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+ | 0.0723 | 35.0 | 35 | 0.3103 | 0.9167 |
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+ | 0.0723 | 36.0 | 36 | 0.2972 | 0.9167 |
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+ | 0.0723 | 37.0 | 37 | 0.2901 | 0.9167 |
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+ | 0.0723 | 38.0 | 38 | 0.2490 | 0.9167 |
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+ | 0.0723 | 39.0 | 39 | 0.2047 | 0.9167 |
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+ | 0.0458 | 40.0 | 40 | 0.1781 | 0.9167 |
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+ | 0.0458 | 41.0 | 41 | 0.1712 | 0.9167 |
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+ | 0.0458 | 42.0 | 42 | 0.2114 | 0.9167 |
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+ | 0.0458 | 43.0 | 43 | 0.2837 | 0.9167 |
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+ | 0.0458 | 44.0 | 44 | 0.3335 | 0.9167 |
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+ | 0.0458 | 45.0 | 45 | 0.3600 | 0.9167 |
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+ | 0.0458 | 46.0 | 46 | 0.3698 | 0.9167 |
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+ | 0.0458 | 47.0 | 47 | 0.3607 | 0.9167 |
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+ | 0.0458 | 48.0 | 48 | 0.3493 | 0.9167 |
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+ | 0.0458 | 49.0 | 49 | 0.3408 | 0.9167 |
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+ | 0.0478 | 50.0 | 50 | 0.3538 | 0.9167 |
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+ | 0.0478 | 51.0 | 51 | 0.3481 | 0.9167 |
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+ | 0.0478 | 52.0 | 52 | 0.3513 | 0.9167 |
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+ | 0.0478 | 53.0 | 53 | 0.3336 | 0.9167 |
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+ | 0.0478 | 54.0 | 54 | 0.3044 | 0.9167 |
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+ | 0.0478 | 55.0 | 55 | 0.2844 | 0.9167 |
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+ | 0.0478 | 56.0 | 56 | 0.2790 | 0.9167 |
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+ | 0.0478 | 57.0 | 57 | 0.2990 | 0.9167 |
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+ | 0.0478 | 58.0 | 58 | 0.3265 | 0.9167 |
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+ | 0.0478 | 59.0 | 59 | 0.3682 | 0.9167 |
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+ | 0.0145 | 60.0 | 60 | 0.3938 | 0.9167 |
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+ | 0.0145 | 61.0 | 61 | 0.4018 | 0.9167 |
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+ | 0.0145 | 62.0 | 62 | 0.3817 | 0.9167 |
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+ | 0.0145 | 63.0 | 63 | 0.3376 | 0.9167 |
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+ | 0.0145 | 64.0 | 64 | 0.2812 | 0.9167 |
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+ | 0.0145 | 65.0 | 65 | 0.2029 | 0.9167 |
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+ | 0.0145 | 66.0 | 66 | 0.1343 | 0.9167 |
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+ | 0.0145 | 67.0 | 67 | 0.0996 | 0.9167 |
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+ | 0.0145 | 68.0 | 68 | 0.0811 | 0.9167 |
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+ | 0.0145 | 69.0 | 69 | 0.0662 | 0.9167 |
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+ | 0.0447 | 70.0 | 70 | 0.0745 | 0.9167 |
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+ | 0.0447 | 71.0 | 71 | 0.1053 | 0.9167 |
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+ | 0.0447 | 72.0 | 72 | 0.1643 | 0.9167 |
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+ | 0.0447 | 73.0 | 73 | 0.2353 | 0.9167 |
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+ | 0.0447 | 74.0 | 74 | 0.3155 | 0.9167 |
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+ | 0.0447 | 75.0 | 75 | 0.3678 | 0.9167 |
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+ | 0.0447 | 76.0 | 76 | 0.3946 | 0.9167 |
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+ | 0.0447 | 77.0 | 77 | 0.4025 | 0.9167 |
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+ | 0.0447 | 78.0 | 78 | 0.4106 | 0.9167 |
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+ | 0.0447 | 79.0 | 79 | 0.4147 | 0.9167 |
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+ | 0.0229 | 80.0 | 80 | 0.4108 | 0.9167 |
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+ | 0.0229 | 81.0 | 81 | 0.3993 | 0.9167 |
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+ | 0.0229 | 82.0 | 82 | 0.3857 | 0.9167 |
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+ | 0.0229 | 83.0 | 83 | 0.3644 | 0.9167 |
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+ | 0.0229 | 84.0 | 84 | 0.3422 | 0.9167 |
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+ | 0.0229 | 85.0 | 85 | 0.3280 | 0.9167 |
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+ | 0.0229 | 86.0 | 86 | 0.3108 | 0.9167 |
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+ | 0.0229 | 87.0 | 87 | 0.2936 | 0.9167 |
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+ | 0.0229 | 88.0 | 88 | 0.2846 | 0.9167 |
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+ | 0.0229 | 89.0 | 89 | 0.2861 | 0.9167 |
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+ | 0.0317 | 90.0 | 90 | 0.2909 | 0.9167 |
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+ | 0.0317 | 91.0 | 91 | 0.2921 | 0.9167 |
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+ | 0.0317 | 92.0 | 92 | 0.2938 | 0.9167 |
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+ | 0.0317 | 93.0 | 93 | 0.2974 | 0.9167 |
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+ | 0.0317 | 94.0 | 94 | 0.2998 | 0.9167 |
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+ | 0.0317 | 95.0 | 95 | 0.2994 | 0.9167 |
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+ | 0.0317 | 96.0 | 96 | 0.2992 | 0.9167 |
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+ | 0.0317 | 97.0 | 97 | 0.2973 | 0.9167 |
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+ | 0.0317 | 98.0 | 98 | 0.2969 | 0.9167 |
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+ | 0.0317 | 99.0 | 99 | 0.2970 | 0.9167 |
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+ | 0.0283 | 100.0 | 100 | 0.2973 | 0.9167 |
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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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