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BEiT-DMAE-13XDA-REVAL-80-32

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  1. README.md +157 -0
  2. all_results.json +12 -0
  3. config.json +77 -0
  4. eval_results.json +8 -0
  5. model.safetensors +3 -0
  6. preprocessor_config.json +28 -0
  7. runs/Dec11_18-55-56_DESKTOP-SKBE9FB/events.out.tfevents.1733964957.DESKTOP-SKBE9FB.18380.0 +3 -0
  8. runs/Dec11_18-55-56_DESKTOP-SKBE9FB/events.out.tfevents.1733972049.DESKTOP-SKBE9FB.18380.1 +3 -0
  9. train_results.json +7 -0
  10. trainer_state.json +3630 -0
  11. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,157 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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-DMAE-13XDA-REVAL-80-32
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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: validation
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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: 0.8478260869565217
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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-DMAE-13XDA-REVAL-80-32
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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: 0.8105
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+ - Accuracy: 0.8478
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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: 3.5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 80
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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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+ | 1.5474 | 1.0 | 60 | 1.2945 | 0.4565 |
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+ | 1.3959 | 1.99 | 120 | 1.2745 | 0.4565 |
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+ | 1.0517 | 2.99 | 180 | 0.9632 | 0.6087 |
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+ | 0.7273 | 4.0 | 241 | 0.7709 | 0.6957 |
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+ | 0.5246 | 5.0 | 301 | 0.7217 | 0.7391 |
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+ | 0.3645 | 5.99 | 361 | 0.7142 | 0.8043 |
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+ | 0.2211 | 6.99 | 421 | 0.6436 | 0.8043 |
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+ | 0.266 | 8.0 | 482 | 1.1316 | 0.6087 |
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+ | 0.1235 | 9.0 | 542 | 0.9257 | 0.7826 |
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+ | 0.1613 | 9.99 | 602 | 0.8527 | 0.7826 |
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+ | 0.0946 | 10.99 | 662 | 0.8274 | 0.8043 |
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+ | 0.1392 | 12.0 | 723 | 0.8312 | 0.7609 |
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+ | 0.1028 | 13.0 | 783 | 1.1959 | 0.7609 |
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+ | 0.1072 | 13.99 | 843 | 1.0017 | 0.7391 |
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+ | 0.0888 | 14.99 | 903 | 0.9214 | 0.8043 |
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+ | 0.0951 | 16.0 | 964 | 0.9156 | 0.7609 |
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+ | 0.0714 | 17.0 | 1024 | 1.3116 | 0.6957 |
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+ | 0.0804 | 17.99 | 1084 | 1.1107 | 0.7826 |
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+ | 0.08 | 18.99 | 1144 | 0.8105 | 0.8478 |
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+ | 0.1619 | 20.0 | 1205 | 0.7581 | 0.8261 |
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+ | 0.084 | 21.0 | 1265 | 1.0210 | 0.8261 |
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+ | 0.072 | 21.99 | 1325 | 1.3092 | 0.7609 |
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+ | 0.0303 | 22.99 | 1385 | 1.3367 | 0.7826 |
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+ | 0.0228 | 24.0 | 1446 | 1.0277 | 0.8261 |
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+ | 0.0755 | 25.0 | 1506 | 0.9436 | 0.8261 |
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+ | 0.0756 | 25.99 | 1566 | 1.1588 | 0.7609 |
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+ | 0.0875 | 26.99 | 1626 | 1.3280 | 0.7174 |
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+ | 0.0771 | 28.0 | 1687 | 1.8558 | 0.6739 |
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+ | 0.0467 | 29.0 | 1747 | 1.6476 | 0.7391 |
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+ | 0.0382 | 29.99 | 1807 | 0.9374 | 0.8478 |
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+ | 0.0511 | 30.99 | 1867 | 1.0847 | 0.8043 |
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+ | 0.0161 | 32.0 | 1928 | 1.2028 | 0.7826 |
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+ | 0.0301 | 33.0 | 1988 | 1.2971 | 0.7391 |
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+ | 0.0443 | 33.99 | 2048 | 1.3993 | 0.7174 |
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+ | 0.0782 | 34.99 | 2108 | 1.3359 | 0.8043 |
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+ | 0.0287 | 36.0 | 2169 | 1.3011 | 0.7826 |
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+ | 0.0347 | 37.0 | 2229 | 1.2450 | 0.7826 |
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+ | 0.0538 | 37.99 | 2289 | 1.8216 | 0.7609 |
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+ | 0.027 | 38.99 | 2349 | 1.1701 | 0.8043 |
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+ | 0.038 | 40.0 | 2410 | 1.1025 | 0.8043 |
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+ | 0.0244 | 41.0 | 2470 | 1.2912 | 0.7609 |
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+ | 0.0122 | 41.99 | 2530 | 1.5699 | 0.7609 |
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+ | 0.023 | 42.99 | 2590 | 1.5114 | 0.7826 |
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+ | 0.0297 | 44.0 | 2651 | 1.2189 | 0.8478 |
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+ | 0.0284 | 45.0 | 2711 | 1.3997 | 0.7826 |
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+ | 0.0203 | 45.99 | 2771 | 1.4792 | 0.8043 |
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+ | 0.03 | 46.99 | 2831 | 1.7487 | 0.7174 |
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+ | 0.025 | 48.0 | 2892 | 1.6605 | 0.7609 |
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+ | 0.0134 | 49.0 | 2952 | 1.4106 | 0.7826 |
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+ | 0.026 | 49.99 | 3012 | 1.2972 | 0.7609 |
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+ | 0.0507 | 50.99 | 3072 | 1.3303 | 0.7826 |
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+ | 0.0394 | 52.0 | 3133 | 1.1954 | 0.8478 |
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+ | 0.0271 | 53.0 | 3193 | 1.3125 | 0.8261 |
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+ | 0.0115 | 53.99 | 3253 | 1.3444 | 0.8478 |
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+ | 0.0138 | 54.99 | 3313 | 1.4689 | 0.8261 |
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+ | 0.0184 | 56.0 | 3374 | 1.4959 | 0.8261 |
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+ | 0.0163 | 57.0 | 3434 | 1.3490 | 0.7826 |
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+ | 0.0112 | 57.99 | 3494 | 1.4749 | 0.7826 |
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+ | 0.0185 | 58.99 | 3554 | 1.5823 | 0.7826 |
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+ | 0.031 | 60.0 | 3615 | 1.5190 | 0.7826 |
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+ | 0.0161 | 61.0 | 3675 | 1.5476 | 0.8043 |
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+ | 0.0146 | 61.99 | 3735 | 1.3930 | 0.7826 |
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+ | 0.005 | 62.99 | 3795 | 1.5454 | 0.8043 |
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+ | 0.0093 | 64.0 | 3856 | 1.5959 | 0.7826 |
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+ | 0.0224 | 65.0 | 3916 | 1.4554 | 0.8043 |
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+ | 0.0154 | 65.99 | 3976 | 1.5327 | 0.8261 |
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+ | 0.0116 | 66.99 | 4036 | 1.6030 | 0.8043 |
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+ | 0.0037 | 68.0 | 4097 | 1.5046 | 0.8261 |
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+ | 0.0023 | 69.0 | 4157 | 1.5222 | 0.8261 |
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+ | 0.0068 | 69.99 | 4217 | 1.4339 | 0.8261 |
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+ | 0.0342 | 70.99 | 4277 | 1.6964 | 0.8043 |
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+ | 0.0077 | 72.0 | 4338 | 1.6102 | 0.8043 |
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+ | 0.0043 | 73.0 | 4398 | 1.6687 | 0.8043 |
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+ | 0.0131 | 73.99 | 4458 | 1.6847 | 0.8043 |
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+ | 0.0031 | 74.99 | 4518 | 1.7195 | 0.8043 |
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+ | 0.0087 | 76.0 | 4579 | 1.7209 | 0.7826 |
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+ | 0.0219 | 77.0 | 4639 | 1.6715 | 0.8043 |
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+ | 0.0229 | 77.99 | 4699 | 1.6823 | 0.8043 |
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+ | 0.008 | 78.99 | 4759 | 1.6751 | 0.8043 |
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+ | 0.0051 | 79.67 | 4800 | 1.6758 | 0.8043 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
all_results.json ADDED
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+ {
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+ "eval_samples_per_second": 55.881,
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+ "eval_steps_per_second": 3.644,
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+ "train_runtime": 7091.3369,
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+ "train_samples_per_second": 43.467,
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+ "train_steps_per_second": 0.677
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+ }
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+ {
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+ "_name_or_path": "microsoft/beit-base-patch16-224",
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+ "add_fpn": false,
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+ "architectures": [
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+ "BeitForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "auxiliary_channels": 256,
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+ "auxiliary_concat_input": false,
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+ "auxiliary_loss_weight": 0.4,
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+ "auxiliary_num_convs": 1,
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+ "drop_path_rate": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "avanzada",
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+ "1": "leve",
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+ "2": "moderada",
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+ "3": "no dmae"
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "beit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "out_features": [
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+ "problem_type": "single_label_classification",
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+ "reshape_hidden_states": true,
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+ "semantic_loss_ignore_index": 255,
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4",
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+ "stage5",
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+ "stage6",
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+ "stage7",
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+ "stage8",
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+ "stage9",
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+ "stage10",
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+ "stage11",
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+ "stage12"
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.36.2",
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+ "use_absolute_position_embeddings": false,
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+ "use_auxiliary_head": true,
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+ "use_mask_token": false,
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+ "use_mean_pooling": true,
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+ "use_relative_position_bias": true,
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+ "use_shared_relative_position_bias": false,
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+ "vocab_size": 8192
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+ }
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