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BilalMuftuoglu
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beit-base-patch16-224-55-fold5

Image Classification
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  2. model.safetensors +1 -1
  3. runs/May20_14-27-57_b94dbfcd7693/events.out.tfevents.1716215278.b94dbfcd7693.1289.7 +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-fold5
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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: 0.7721518987341772
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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-fold5
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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: 0.9050
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+ - Accuracy: 0.7722
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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 | 0.8571 | 3 | 0.6964 | 0.4937 |
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+ | No log | 2.0 | 7 | 0.6336 | 0.6456 |
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+ | 0.7161 | 2.8571 | 10 | 0.6712 | 0.5063 |
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+ | 0.7161 | 4.0 | 14 | 0.5884 | 0.6835 |
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+ | 0.7161 | 4.8571 | 17 | 0.6325 | 0.5570 |
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+ | 0.6466 | 6.0 | 21 | 0.6307 | 0.6076 |
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+ | 0.6466 | 6.8571 | 24 | 0.5518 | 0.6835 |
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+ | 0.6466 | 8.0 | 28 | 0.6856 | 0.6456 |
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+ | 0.5604 | 8.8571 | 31 | 0.5678 | 0.7089 |
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+ | 0.5604 | 10.0 | 35 | 0.5764 | 0.6329 |
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+ | 0.5604 | 10.8571 | 38 | 0.6124 | 0.6456 |
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+ | 0.4941 | 12.0 | 42 | 1.1315 | 0.5316 |
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+ | 0.4941 | 12.8571 | 45 | 0.5624 | 0.6835 |
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+ | 0.4941 | 14.0 | 49 | 0.6351 | 0.6962 |
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+ | 0.4516 | 14.8571 | 52 | 0.6811 | 0.6835 |
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+ | 0.4516 | 16.0 | 56 | 0.7385 | 0.6456 |
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+ | 0.4516 | 16.8571 | 59 | 0.6123 | 0.7215 |
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+ | 0.409 | 18.0 | 63 | 0.5877 | 0.6835 |
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+ | 0.409 | 18.8571 | 66 | 0.6250 | 0.6962 |
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+ | 0.3439 | 20.0 | 70 | 0.6220 | 0.7342 |
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+ | 0.3439 | 20.8571 | 73 | 0.7250 | 0.7089 |
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+ | 0.3439 | 22.0 | 77 | 0.6107 | 0.7342 |
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+ | 0.3268 | 22.8571 | 80 | 0.4999 | 0.7975 |
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+ | 0.3268 | 24.0 | 84 | 0.5325 | 0.7468 |
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+ | 0.3268 | 24.8571 | 87 | 0.7209 | 0.7342 |
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+ | 0.2941 | 26.0 | 91 | 0.5557 | 0.7722 |
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+ | 0.2941 | 26.8571 | 94 | 0.6655 | 0.7595 |
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+ | 0.2941 | 28.0 | 98 | 1.0775 | 0.6962 |
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+ | 0.284 | 28.8571 | 101 | 0.6817 | 0.7595 |
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+ | 0.284 | 30.0 | 105 | 0.9235 | 0.6835 |
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+ | 0.284 | 30.8571 | 108 | 0.6587 | 0.7595 |
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+ | 0.3134 | 32.0 | 112 | 0.7086 | 0.7468 |
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+ | 0.3134 | 32.8571 | 115 | 0.6895 | 0.7468 |
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+ | 0.3134 | 34.0 | 119 | 0.6418 | 0.7722 |
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+ | 0.2266 | 34.8571 | 122 | 0.7007 | 0.7848 |
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+ | 0.2266 | 36.0 | 126 | 0.6919 | 0.8228 |
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+ | 0.2266 | 36.8571 | 129 | 0.7562 | 0.7342 |
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+ | 0.2249 | 38.0 | 133 | 0.6775 | 0.7722 |
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+ | 0.2249 | 38.8571 | 136 | 0.7787 | 0.7595 |
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+ | 0.2181 | 40.0 | 140 | 0.7932 | 0.7722 |
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+ | 0.2181 | 40.8571 | 143 | 0.9334 | 0.7595 |
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+ | 0.2181 | 42.0 | 147 | 0.8224 | 0.7468 |
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+ | 0.186 | 42.8571 | 150 | 0.8444 | 0.7722 |
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+ | 0.186 | 44.0 | 154 | 1.0350 | 0.7722 |
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+ | 0.186 | 44.8571 | 157 | 0.8386 | 0.7722 |
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+ | 0.1882 | 46.0 | 161 | 0.8384 | 0.7722 |
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+ | 0.1882 | 46.8571 | 164 | 0.7905 | 0.7595 |
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+ | 0.1882 | 48.0 | 168 | 0.7184 | 0.7722 |
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+ | 0.1649 | 48.8571 | 171 | 0.8119 | 0.7595 |
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+ | 0.1649 | 50.0 | 175 | 0.7172 | 0.7722 |
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+ | 0.1649 | 50.8571 | 178 | 0.9249 | 0.7722 |
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+ | 0.1847 | 52.0 | 182 | 0.8069 | 0.7722 |
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+ | 0.1847 | 52.8571 | 185 | 0.8753 | 0.7722 |
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+ | 0.1847 | 54.0 | 189 | 0.8822 | 0.7722 |
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+ | 0.1606 | 54.8571 | 192 | 0.7481 | 0.7975 |
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+ | 0.1606 | 56.0 | 196 | 0.7300 | 0.7722 |
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+ | 0.1606 | 56.8571 | 199 | 0.7325 | 0.8101 |
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+ | 0.142 | 58.0 | 203 | 0.7088 | 0.8228 |
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+ | 0.142 | 58.8571 | 206 | 0.6900 | 0.8228 |
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+ | 0.1546 | 60.0 | 210 | 0.8303 | 0.7722 |
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+ | 0.1546 | 60.8571 | 213 | 0.8218 | 0.7975 |
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+ | 0.1546 | 62.0 | 217 | 0.9628 | 0.7848 |
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+ | 0.1608 | 62.8571 | 220 | 0.9826 | 0.7848 |
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+ | 0.1608 | 64.0 | 224 | 0.7604 | 0.7595 |
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+ | 0.1608 | 64.8571 | 227 | 0.8165 | 0.7722 |
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+ | 0.1418 | 66.0 | 231 | 0.8280 | 0.7722 |
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+ | 0.1418 | 66.8571 | 234 | 0.9254 | 0.7848 |
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+ | 0.1418 | 68.0 | 238 | 0.8439 | 0.7848 |
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+ | 0.1505 | 68.8571 | 241 | 0.8096 | 0.7975 |
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+ | 0.1505 | 70.0 | 245 | 0.9471 | 0.7595 |
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+ | 0.1505 | 70.8571 | 248 | 0.9028 | 0.7595 |
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+ | 0.1211 | 72.0 | 252 | 0.7744 | 0.7975 |
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+ | 0.1211 | 72.8571 | 255 | 0.7756 | 0.8101 |
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+ | 0.1211 | 74.0 | 259 | 0.7904 | 0.8101 |
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+ | 0.1248 | 74.8571 | 262 | 0.8036 | 0.8101 |
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+ | 0.1248 | 76.0 | 266 | 0.8592 | 0.7848 |
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+ | 0.1248 | 76.8571 | 269 | 0.8946 | 0.7848 |
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+ | 0.122 | 78.0 | 273 | 0.8576 | 0.7848 |
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+ | 0.122 | 78.8571 | 276 | 0.9037 | 0.7975 |
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+ | 0.1129 | 80.0 | 280 | 0.9982 | 0.7848 |
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+ | 0.1129 | 80.8571 | 283 | 1.0404 | 0.7722 |
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+ | 0.1129 | 82.0 | 287 | 0.9969 | 0.7975 |
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+ | 0.1136 | 82.8571 | 290 | 0.9586 | 0.7975 |
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+ | 0.1136 | 84.0 | 294 | 0.9200 | 0.7848 |
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+ | 0.1136 | 84.8571 | 297 | 0.9063 | 0.7722 |
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+ | 0.1233 | 85.7143 | 300 | 0.9050 | 0.7722 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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