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jordyvl
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dit_maveriq_tobacco3482_2023-07-04_noaccum

Image Classification
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PyTorch
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Generated from Trainer
Inference Endpoints
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: dit_maveriq_tobacco3482_2023-07-04_noaccum
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+ results: []
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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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+ # dit_maveriq_tobacco3482_2023-07-04_noaccum
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+
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+ This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3767
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+ - Accuracy: 0.95
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 4
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+ - seed: 42
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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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+ - 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 | 25 | 1.6738 | 0.405 |
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+ | No log | 2.0 | 50 | 1.2848 | 0.605 |
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+ | No log | 3.0 | 75 | 0.9015 | 0.74 |
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+ | No log | 4.0 | 100 | 0.6159 | 0.79 |
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+ | No log | 5.0 | 125 | 0.4341 | 0.85 |
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+ | No log | 6.0 | 150 | 0.3338 | 0.885 |
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+ | No log | 7.0 | 175 | 0.3210 | 0.89 |
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+ | No log | 8.0 | 200 | 0.3121 | 0.915 |
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+ | No log | 9.0 | 225 | 0.3235 | 0.915 |
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+ | No log | 10.0 | 250 | 0.3003 | 0.92 |
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+ | No log | 11.0 | 275 | 0.2602 | 0.94 |
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+ | No log | 12.0 | 300 | 0.2892 | 0.94 |
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+ | No log | 13.0 | 325 | 0.2865 | 0.945 |
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+ | No log | 14.0 | 350 | 0.3103 | 0.94 |
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+ | No log | 15.0 | 375 | 0.2959 | 0.955 |
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+ | No log | 16.0 | 400 | 0.3026 | 0.94 |
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+ | No log | 17.0 | 425 | 0.3082 | 0.94 |
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+ | No log | 18.0 | 450 | 0.2951 | 0.94 |
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+ | No log | 19.0 | 475 | 0.3310 | 0.94 |
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+ | 0.4279 | 20.0 | 500 | 0.3335 | 0.95 |
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+ | 0.4279 | 21.0 | 525 | 0.3035 | 0.94 |
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+ | 0.4279 | 22.0 | 550 | 0.3155 | 0.945 |
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+ | 0.4279 | 23.0 | 575 | 0.3539 | 0.945 |
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+ | 0.4279 | 24.0 | 600 | 0.3359 | 0.95 |
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+ | 0.4279 | 25.0 | 625 | 0.3887 | 0.945 |
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+ | 0.4279 | 26.0 | 650 | 0.3998 | 0.935 |
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+ | 0.4279 | 27.0 | 675 | 0.4087 | 0.94 |
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+ | 0.4279 | 28.0 | 700 | 0.4065 | 0.93 |
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+ | 0.4279 | 29.0 | 725 | 0.3713 | 0.935 |
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+ | 0.4279 | 30.0 | 750 | 0.3547 | 0.945 |
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+ | 0.4279 | 31.0 | 775 | 0.3757 | 0.93 |
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+ | 0.4279 | 32.0 | 800 | 0.3613 | 0.945 |
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+ | 0.4279 | 33.0 | 825 | 0.3686 | 0.945 |
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+ | 0.4279 | 34.0 | 850 | 0.3254 | 0.945 |
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+ | 0.4279 | 35.0 | 875 | 0.3514 | 0.95 |
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+ | 0.4279 | 36.0 | 900 | 0.3061 | 0.95 |
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+ | 0.4279 | 37.0 | 925 | 0.3339 | 0.94 |
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+ | 0.4279 | 38.0 | 950 | 0.3241 | 0.955 |
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+ | 0.4279 | 39.0 | 975 | 0.2779 | 0.955 |
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+ | 0.029 | 40.0 | 1000 | 0.2788 | 0.955 |
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+ | 0.029 | 41.0 | 1025 | 0.2993 | 0.95 |
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+ | 0.029 | 42.0 | 1050 | 0.3171 | 0.955 |
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+ | 0.029 | 43.0 | 1075 | 0.3340 | 0.95 |
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+ | 0.029 | 44.0 | 1100 | 0.3463 | 0.955 |
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+ | 0.029 | 45.0 | 1125 | 0.3417 | 0.955 |
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+ | 0.029 | 46.0 | 1150 | 0.3377 | 0.96 |
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+ | 0.029 | 47.0 | 1175 | 0.3424 | 0.945 |
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+ | 0.029 | 48.0 | 1200 | 0.3377 | 0.95 |
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+ | 0.029 | 49.0 | 1225 | 0.3731 | 0.935 |
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+ | 0.029 | 50.0 | 1250 | 0.3719 | 0.95 |
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+ | 0.029 | 51.0 | 1275 | 0.3615 | 0.945 |
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+ | 0.029 | 52.0 | 1300 | 0.3473 | 0.955 |
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+ | 0.029 | 53.0 | 1325 | 0.3427 | 0.945 |
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+ | 0.029 | 54.0 | 1350 | 0.4078 | 0.94 |
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+ | 0.029 | 55.0 | 1375 | 0.3763 | 0.955 |
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+ | 0.029 | 56.0 | 1400 | 0.3844 | 0.945 |
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+ | 0.029 | 57.0 | 1425 | 0.3845 | 0.945 |
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+ | 0.029 | 58.0 | 1450 | 0.3976 | 0.94 |
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+ | 0.029 | 59.0 | 1475 | 0.3636 | 0.95 |
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+ | 0.0115 | 60.0 | 1500 | 0.3431 | 0.95 |
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+ | 0.0115 | 61.0 | 1525 | 0.3161 | 0.955 |
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+ | 0.0115 | 62.0 | 1550 | 0.3482 | 0.945 |
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+ | 0.0115 | 63.0 | 1575 | 0.3693 | 0.945 |
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+ | 0.0115 | 64.0 | 1600 | 0.3435 | 0.95 |
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+ | 0.0115 | 65.0 | 1625 | 0.3403 | 0.955 |
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+ | 0.0115 | 66.0 | 1650 | 0.3644 | 0.95 |
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+ | 0.0115 | 67.0 | 1675 | 0.3604 | 0.955 |
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+ | 0.0115 | 68.0 | 1700 | 0.3746 | 0.945 |
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+ | 0.0115 | 69.0 | 1725 | 0.3899 | 0.94 |
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+ | 0.0115 | 70.0 | 1750 | 0.3684 | 0.95 |
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+ | 0.0115 | 71.0 | 1775 | 0.4124 | 0.94 |
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+ | 0.0115 | 72.0 | 1800 | 0.4010 | 0.95 |
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+ | 0.0115 | 73.0 | 1825 | 0.3991 | 0.95 |
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+ | 0.0115 | 74.0 | 1850 | 0.3859 | 0.95 |
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+ | 0.0115 | 75.0 | 1875 | 0.3832 | 0.96 |
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+ | 0.0115 | 76.0 | 1900 | 0.4054 | 0.955 |
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+ | 0.0115 | 77.0 | 1925 | 0.4119 | 0.955 |
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+ | 0.0115 | 78.0 | 1950 | 0.3724 | 0.955 |
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+ | 0.0115 | 79.0 | 1975 | 0.3609 | 0.95 |
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+ | 0.0116 | 80.0 | 2000 | 0.3663 | 0.955 |
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+ | 0.0116 | 81.0 | 2025 | 0.3711 | 0.955 |
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+ | 0.0116 | 82.0 | 2050 | 0.3730 | 0.955 |
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+ | 0.0116 | 83.0 | 2075 | 0.3775 | 0.955 |
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+ | 0.0116 | 84.0 | 2100 | 0.3805 | 0.96 |
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+ | 0.0116 | 85.0 | 2125 | 0.3802 | 0.96 |
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+ | 0.0116 | 86.0 | 2150 | 0.3773 | 0.96 |
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+ | 0.0116 | 87.0 | 2175 | 0.3684 | 0.955 |
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+ | 0.0116 | 88.0 | 2200 | 0.3750 | 0.95 |
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+ | 0.0116 | 89.0 | 2225 | 0.3727 | 0.945 |
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+ | 0.0116 | 90.0 | 2250 | 0.3742 | 0.945 |
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+ | 0.0116 | 91.0 | 2275 | 0.3729 | 0.945 |
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+ | 0.0116 | 92.0 | 2300 | 0.3727 | 0.945 |
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+ | 0.0116 | 93.0 | 2325 | 0.3752 | 0.95 |
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+ | 0.0116 | 94.0 | 2350 | 0.3726 | 0.945 |
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+ | 0.0116 | 95.0 | 2375 | 0.3738 | 0.945 |
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+ | 0.0116 | 96.0 | 2400 | 0.3747 | 0.945 |
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+ | 0.0116 | 97.0 | 2425 | 0.3755 | 0.945 |
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+ | 0.0116 | 98.0 | 2450 | 0.3757 | 0.95 |
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+ | 0.0116 | 99.0 | 2475 | 0.3764 | 0.95 |
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+ | 0.0061 | 100.0 | 2500 | 0.3767 | 0.95 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1.post200
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+ - Datasets 2.9.0
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+ - Tokenizers 0.13.2