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BilalMuftuoglu
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beit-base-patch16-224-hasta-85-fold3

Image Classification
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  2. model.safetensors +1 -1
  3. runs/May23_15-27-11_2bc4f829fe52/events.out.tfevents.1716478033.2bc4f829fe52.989.34 +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-fold3
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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-fold3
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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: 2.4788
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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 | 1.3301 | 0.1818 |
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+ | No log | 2.0 | 2 | 1.1012 | 0.3636 |
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+ | No log | 3.0 | 3 | 0.8911 | 0.7273 |
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+ | No log | 4.0 | 4 | 0.9555 | 0.7273 |
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+ | No log | 5.0 | 5 | 1.2582 | 0.7273 |
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+ | No log | 6.0 | 6 | 1.5576 | 0.7273 |
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+ | No log | 7.0 | 7 | 1.6687 | 0.7273 |
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+ | No log | 8.0 | 8 | 1.5015 | 0.7273 |
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+ | No log | 9.0 | 9 | 1.2729 | 0.7273 |
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+ | 0.3584 | 10.0 | 10 | 1.2127 | 0.7273 |
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+ | 0.3584 | 11.0 | 11 | 1.3132 | 0.7273 |
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+ | 0.3584 | 12.0 | 12 | 1.3350 | 0.7273 |
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+ | 0.3584 | 13.0 | 13 | 1.2579 | 0.7273 |
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+ | 0.3584 | 14.0 | 14 | 1.3559 | 0.7273 |
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+ | 0.3584 | 15.0 | 15 | 1.4231 | 0.7273 |
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+ | 0.3584 | 16.0 | 16 | 1.5141 | 0.7273 |
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+ | 0.3584 | 17.0 | 17 | 1.4200 | 0.7273 |
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+ | 0.3584 | 18.0 | 18 | 1.2498 | 0.7273 |
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+ | 0.3584 | 19.0 | 19 | 1.1456 | 0.7273 |
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+ | 0.1919 | 20.0 | 20 | 1.1055 | 0.7273 |
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+ | 0.1919 | 21.0 | 21 | 1.1937 | 0.7273 |
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+ | 0.1919 | 22.0 | 22 | 1.2768 | 0.7273 |
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+ | 0.1919 | 23.0 | 23 | 1.3224 | 0.7273 |
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+ | 0.1919 | 24.0 | 24 | 1.3629 | 0.7273 |
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+ | 0.1919 | 25.0 | 25 | 1.3238 | 0.7273 |
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+ | 0.1919 | 26.0 | 26 | 1.2280 | 0.7273 |
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+ | 0.1919 | 27.0 | 27 | 1.2446 | 0.7273 |
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+ | 0.1919 | 28.0 | 28 | 1.2530 | 0.7273 |
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+ | 0.1919 | 29.0 | 29 | 1.2468 | 0.7273 |
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+ | 0.1447 | 30.0 | 30 | 1.1535 | 0.7273 |
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+ | 0.1447 | 31.0 | 31 | 1.1125 | 0.7273 |
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+ | 0.1447 | 32.0 | 32 | 1.2051 | 0.7273 |
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+ | 0.1447 | 33.0 | 33 | 1.5902 | 0.7273 |
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+ | 0.1447 | 34.0 | 34 | 1.8445 | 0.7273 |
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+ | 0.1447 | 35.0 | 35 | 1.7222 | 0.7273 |
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+ | 0.1447 | 36.0 | 36 | 1.5080 | 0.7273 |
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+ | 0.1447 | 37.0 | 37 | 1.3542 | 0.7273 |
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+ | 0.1447 | 38.0 | 38 | 1.3106 | 0.7273 |
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+ | 0.1447 | 39.0 | 39 | 1.4533 | 0.7273 |
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+ | 0.1053 | 40.0 | 40 | 1.6427 | 0.7273 |
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+ | 0.1053 | 41.0 | 41 | 1.7518 | 0.7273 |
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+ | 0.1053 | 42.0 | 42 | 1.7775 | 0.7273 |
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+ | 0.1053 | 43.0 | 43 | 1.6831 | 0.7273 |
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+ | 0.1053 | 44.0 | 44 | 1.6968 | 0.7273 |
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+ | 0.1053 | 45.0 | 45 | 1.8236 | 0.7273 |
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+ | 0.1053 | 46.0 | 46 | 1.8845 | 0.7273 |
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+ | 0.1053 | 47.0 | 47 | 1.8785 | 0.7273 |
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+ | 0.1053 | 48.0 | 48 | 1.8805 | 0.7273 |
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+ | 0.1053 | 49.0 | 49 | 1.9625 | 0.7273 |
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+ | 0.0771 | 50.0 | 50 | 1.9860 | 0.7273 |
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+ | 0.0771 | 51.0 | 51 | 1.9708 | 0.7273 |
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+ | 0.0771 | 52.0 | 52 | 1.9149 | 0.7273 |
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+ | 0.0771 | 53.0 | 53 | 1.9064 | 0.7273 |
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+ | 0.0771 | 54.0 | 54 | 1.8804 | 0.7273 |
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+ | 0.0771 | 55.0 | 55 | 1.8467 | 0.7273 |
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+ | 0.0771 | 56.0 | 56 | 1.8508 | 0.7273 |
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+ | 0.0771 | 57.0 | 57 | 1.8675 | 0.7273 |
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+ | 0.0771 | 58.0 | 58 | 1.8886 | 0.7273 |
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+ | 0.0771 | 59.0 | 59 | 1.8860 | 0.7273 |
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+ | 0.0528 | 60.0 | 60 | 1.8777 | 0.7273 |
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+ | 0.0528 | 61.0 | 61 | 1.9119 | 0.7273 |
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+ | 0.0528 | 62.0 | 62 | 1.9860 | 0.7273 |
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+ | 0.0528 | 63.0 | 63 | 2.1003 | 0.7273 |
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+ | 0.0528 | 64.0 | 64 | 2.1561 | 0.7273 |
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+ | 0.0528 | 65.0 | 65 | 2.1454 | 0.7273 |
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+ | 0.0528 | 66.0 | 66 | 2.0685 | 0.7273 |
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+ | 0.0528 | 67.0 | 67 | 1.9261 | 0.7273 |
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+ | 0.0528 | 68.0 | 68 | 1.6839 | 0.7273 |
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+ | 0.0528 | 69.0 | 69 | 1.4306 | 0.7273 |
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+ | 0.043 | 70.0 | 70 | 1.3800 | 0.7273 |
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+ | 0.043 | 71.0 | 71 | 1.4814 | 0.7273 |
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+ | 0.043 | 72.0 | 72 | 1.6014 | 0.7273 |
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+ | 0.043 | 73.0 | 73 | 1.7792 | 0.7273 |
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+ | 0.043 | 74.0 | 74 | 1.9423 | 0.7273 |
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+ | 0.043 | 75.0 | 75 | 2.0590 | 0.7273 |
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+ | 0.043 | 76.0 | 76 | 2.1119 | 0.7273 |
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+ | 0.043 | 77.0 | 77 | 2.1116 | 0.7273 |
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+ | 0.043 | 78.0 | 78 | 2.0979 | 0.7273 |
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+ | 0.043 | 79.0 | 79 | 2.1457 | 0.7273 |
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+ | 0.0429 | 80.0 | 80 | 2.2222 | 0.7273 |
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+ | 0.0429 | 81.0 | 81 | 2.2803 | 0.7273 |
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+ | 0.0429 | 82.0 | 82 | 2.3327 | 0.7273 |
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+ | 0.0429 | 83.0 | 83 | 2.3643 | 0.7273 |
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+ | 0.0429 | 84.0 | 84 | 2.3774 | 0.7273 |
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+ | 0.0429 | 85.0 | 85 | 2.3838 | 0.7273 |
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+ | 0.0429 | 86.0 | 86 | 2.4072 | 0.7273 |
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+ | 0.0429 | 87.0 | 87 | 2.4189 | 0.7273 |
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+ | 0.0429 | 88.0 | 88 | 2.4028 | 0.7273 |
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+ | 0.0429 | 89.0 | 89 | 2.3847 | 0.7273 |
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+ | 0.0475 | 90.0 | 90 | 2.3793 | 0.7273 |
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+ | 0.0475 | 91.0 | 91 | 2.3831 | 0.7273 |
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+ | 0.0475 | 92.0 | 92 | 2.3882 | 0.7273 |
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+ | 0.0475 | 93.0 | 93 | 2.3964 | 0.7273 |
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+ | 0.0475 | 94.0 | 94 | 2.4126 | 0.7273 |
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+ | 0.0475 | 95.0 | 95 | 2.4309 | 0.7273 |
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+ | 0.0475 | 96.0 | 96 | 2.4486 | 0.7273 |
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+ | 0.0475 | 97.0 | 97 | 2.4628 | 0.7273 |
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+ | 0.0475 | 98.0 | 98 | 2.4723 | 0.7273 |
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+ | 0.0475 | 99.0 | 99 | 2.4775 | 0.7273 |
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+ | 0.0337 | 100.0 | 100 | 2.4788 | 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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