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BEiT-DMAE-XDA-REVAL-80

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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_12-32-26_DESKTOP-SKBE9FB/events.out.tfevents.1733941947.DESKTOP-SKBE9FB.9872.0 +3 -0
  8. runs/Dec11_12-56-53_DESKTOP-SKBE9FB/events.out.tfevents.1733943417.DESKTOP-SKBE9FB.19636.0 +3 -0
  9. runs/Dec11_12-56-53_DESKTOP-SKBE9FB/events.out.tfevents.1733950237.DESKTOP-SKBE9FB.19636.1 +3 -0
  10. train_results.json +7 -0
  11. trainer_state.json +3630 -0
  12. training_args.bin +3 -0
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-DMAE-XDA-REVAL-80
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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: 0.8043478260869565
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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-XDA-REVAL-80
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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: 1.2505
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+ - Accuracy: 0.8043
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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: 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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+ | 1.5404 | 1.0 | 60 | 1.2860 | 0.4565 |
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+ | 1.2921 | 2.0 | 120 | 1.1580 | 0.4783 |
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+ | 0.8862 | 3.0 | 180 | 0.9703 | 0.4783 |
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+ | 0.5719 | 4.0 | 240 | 0.8845 | 0.6957 |
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+ | 0.3656 | 5.0 | 300 | 0.7957 | 0.7174 |
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+ | 0.2146 | 6.0 | 360 | 0.8632 | 0.6957 |
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+ | 0.182 | 7.0 | 420 | 1.0534 | 0.6739 |
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+ | 0.1809 | 8.0 | 480 | 1.1159 | 0.7609 |
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+ | 0.1687 | 9.0 | 540 | 0.7967 | 0.7609 |
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+ | 0.1798 | 10.0 | 600 | 1.1140 | 0.6957 |
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+ | 0.1961 | 11.0 | 660 | 1.6409 | 0.5870 |
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+ | 0.1475 | 12.0 | 720 | 1.4891 | 0.6739 |
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+ | 0.0964 | 13.0 | 780 | 1.6115 | 0.6739 |
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+ | 0.0797 | 14.0 | 840 | 1.4461 | 0.6739 |
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+ | 0.069 | 15.0 | 900 | 1.3023 | 0.6957 |
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+ | 0.0937 | 16.0 | 960 | 1.2890 | 0.6957 |
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+ | 0.105 | 17.0 | 1020 | 1.1601 | 0.7609 |
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+ | 0.0909 | 18.0 | 1080 | 1.0927 | 0.7609 |
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+ | 0.0561 | 19.0 | 1140 | 1.4284 | 0.7391 |
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+ | 0.102 | 20.0 | 1200 | 1.4661 | 0.6739 |
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+ | 0.0632 | 21.0 | 1260 | 1.2734 | 0.7174 |
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+ | 0.0396 | 22.0 | 1320 | 1.8164 | 0.6522 |
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+ | 0.0831 | 23.0 | 1380 | 1.5103 | 0.7391 |
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+ | 0.0696 | 24.0 | 1440 | 1.6661 | 0.6739 |
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+ | 0.0787 | 25.0 | 1500 | 1.5281 | 0.7391 |
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+ | 0.0318 | 26.0 | 1560 | 1.4044 | 0.7609 |
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+ | 0.056 | 27.0 | 1620 | 1.2505 | 0.8043 |
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+ | 0.0379 | 28.0 | 1680 | 1.4474 | 0.7174 |
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+ | 0.0475 | 29.0 | 1740 | 1.6855 | 0.6957 |
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+ | 0.0315 | 30.0 | 1800 | 1.3772 | 0.7609 |
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+ | 0.0661 | 31.0 | 1860 | 1.7190 | 0.6522 |
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+ | 0.0401 | 32.0 | 1920 | 1.2325 | 0.8043 |
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+ | 0.0503 | 33.0 | 1980 | 1.6231 | 0.7174 |
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+ | 0.0585 | 34.0 | 2040 | 1.4190 | 0.7609 |
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+ | 0.0338 | 35.0 | 2100 | 1.3640 | 0.7391 |
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+ | 0.0343 | 36.0 | 2160 | 2.1224 | 0.6304 |
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+ | 0.064 | 37.0 | 2220 | 2.0131 | 0.6739 |
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+ | 0.0253 | 38.0 | 2280 | 1.8281 | 0.7391 |
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+ | 0.0435 | 39.0 | 2340 | 1.4020 | 0.6957 |
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+ | 0.0344 | 40.0 | 2400 | 1.4519 | 0.7391 |
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+ | 0.0114 | 41.0 | 2460 | 1.8910 | 0.6957 |
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+ | 0.0366 | 42.0 | 2520 | 1.3172 | 0.7609 |
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+ | 0.0331 | 43.0 | 2580 | 1.3786 | 0.7391 |
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+ | 0.0298 | 44.0 | 2640 | 1.3052 | 0.7391 |
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+ | 0.0426 | 45.0 | 2700 | 1.2308 | 0.7826 |
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+ | 0.0259 | 46.0 | 2760 | 1.6801 | 0.7391 |
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+ | 0.0181 | 47.0 | 2820 | 1.6076 | 0.7174 |
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+ | 0.0266 | 48.0 | 2880 | 1.4670 | 0.7826 |
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+ | 0.0239 | 49.0 | 2940 | 1.4582 | 0.7174 |
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+ | 0.0174 | 50.0 | 3000 | 1.4778 | 0.7826 |
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+ | 0.0365 | 51.0 | 3060 | 1.7034 | 0.7174 |
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+ | 0.0124 | 52.0 | 3120 | 2.0013 | 0.7174 |
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+ | 0.0299 | 53.0 | 3180 | 1.8081 | 0.7174 |
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+ | 0.0042 | 54.0 | 3240 | 1.6417 | 0.7391 |
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+ | 0.0305 | 55.0 | 3300 | 1.7993 | 0.7391 |
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+ | 0.026 | 56.0 | 3360 | 2.2341 | 0.7174 |
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+ | 0.0207 | 57.0 | 3420 | 1.6739 | 0.7391 |
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+ | 0.0063 | 58.0 | 3480 | 1.8008 | 0.7174 |
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+ | 0.0052 | 59.0 | 3540 | 2.1553 | 0.6957 |
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+ | 0.0061 | 60.0 | 3600 | 2.1446 | 0.6957 |
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+ | 0.0017 | 61.0 | 3660 | 2.2132 | 0.6957 |
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+ | 0.0143 | 62.0 | 3720 | 1.7295 | 0.7174 |
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+ | 0.004 | 63.0 | 3780 | 1.5038 | 0.8043 |
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+ | 0.0164 | 64.0 | 3840 | 1.5734 | 0.7609 |
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+ | 0.0105 | 65.0 | 3900 | 1.6073 | 0.7174 |
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+ | 0.0161 | 66.0 | 3960 | 1.6313 | 0.7391 |
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+ | 0.0073 | 67.0 | 4020 | 1.7684 | 0.7391 |
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+ | 0.004 | 68.0 | 4080 | 1.5423 | 0.7609 |
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+ | 0.0096 | 69.0 | 4140 | 1.8458 | 0.7174 |
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+ | 0.0279 | 70.0 | 4200 | 2.0681 | 0.6739 |
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+ | 0.0067 | 71.0 | 4260 | 2.0441 | 0.6739 |
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+ | 0.0145 | 72.0 | 4320 | 2.1306 | 0.6957 |
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+ | 0.0084 | 73.0 | 4380 | 2.0877 | 0.6957 |
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+ | 0.0068 | 74.0 | 4440 | 2.1404 | 0.6957 |
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+ | 0.0044 | 75.0 | 4500 | 2.1604 | 0.6957 |
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+ | 0.0143 | 76.0 | 4560 | 2.1835 | 0.6957 |
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+ | 0.0105 | 77.0 | 4620 | 2.2572 | 0.6739 |
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+ | 0.0036 | 78.0 | 4680 | 2.2357 | 0.6739 |
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+ | 0.0205 | 79.0 | 4740 | 2.2578 | 0.6739 |
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+ | 0.0095 | 80.0 | 4800 | 2.2530 | 0.6739 |
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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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+ "epoch": 80.0,
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+ "eval_accuracy": 0.8043478260869565,
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+ "eval_samples_per_second": 55.293,
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+ "eval_steps_per_second": 3.606,
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+ "train_loss": 0.11213935243470284,
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+ "train_runtime": 6818.2753,
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+ "train_samples_per_second": 44.926,
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+ "train_steps_per_second": 0.704
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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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+ "initializer_range": 0.02,
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+ "layer_norm_eps": 1e-12,
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+ "layer_scale_init_value": 0.1,
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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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+ "stage12"
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+ "out_indices": [
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+ 12
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+ "patch_size": 16,
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+ "pool_scales": [
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+ 1,
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+ 2,
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+ 6
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+ ],
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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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+ ],
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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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