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dit-small_tobacco3482_kd_CEKD_t2.5_a0.7

Image Classification
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PyTorch
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Generated from Trainer
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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-small_tobacco3482_kd_CEKD_t2.5_a0.7
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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-small_tobacco3482_kd_CEKD_t2.5_a0.7
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.1993
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+ - Accuracy: 0.185
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+ - Brier Loss: 0.8672
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+ - Nll: 6.5703
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+ - F1 Micro: 0.185
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+ - F1 Macro: 0.0488
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+ - Ece: 0.2594
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+ - Aurc: 0.7367
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 256
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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: 25
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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 | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
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+ | No log | 0.96 | 3 | 3.4684 | 0.06 | 0.9042 | 9.2910 | 0.06 | 0.0114 | 0.1755 | 0.9033 |
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+ | No log | 1.96 | 6 | 3.3741 | 0.18 | 0.8886 | 6.5491 | 0.18 | 0.0305 | 0.2324 | 0.8055 |
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+ | No log | 2.96 | 9 | 3.2779 | 0.18 | 0.8767 | 7.2662 | 0.18 | 0.0305 | 0.2493 | 0.8196 |
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+ | No log | 3.96 | 12 | 3.2605 | 0.18 | 0.8816 | 7.0963 | 0.18 | 0.0305 | 0.2628 | 0.8140 |
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+ | No log | 4.96 | 15 | 3.2592 | 0.185 | 0.8814 | 6.9350 | 0.185 | 0.0488 | 0.2584 | 0.7850 |
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+ | No log | 5.96 | 18 | 3.2576 | 0.185 | 0.8782 | 6.3113 | 0.185 | 0.0488 | 0.2561 | 0.7731 |
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+ | No log | 6.96 | 21 | 3.2540 | 0.185 | 0.8747 | 6.0058 | 0.185 | 0.0488 | 0.2446 | 0.7705 |
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+ | No log | 7.96 | 24 | 3.2500 | 0.185 | 0.8731 | 5.9849 | 0.185 | 0.0488 | 0.2442 | 0.7669 |
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+ | No log | 8.96 | 27 | 3.2430 | 0.185 | 0.8717 | 5.9785 | 0.185 | 0.0488 | 0.2483 | 0.7626 |
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+ | No log | 9.96 | 30 | 3.2377 | 0.185 | 0.8711 | 6.2837 | 0.185 | 0.0488 | 0.2462 | 0.7609 |
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+ | No log | 10.96 | 33 | 3.2332 | 0.185 | 0.8713 | 6.8641 | 0.185 | 0.0488 | 0.2560 | 0.7601 |
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+ | No log | 11.96 | 36 | 3.2293 | 0.185 | 0.8719 | 6.8631 | 0.185 | 0.0488 | 0.2523 | 0.7587 |
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+ | No log | 12.96 | 39 | 3.2246 | 0.185 | 0.8717 | 6.8535 | 0.185 | 0.0488 | 0.2526 | 0.7558 |
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+ | No log | 13.96 | 42 | 3.2190 | 0.185 | 0.8709 | 6.8177 | 0.185 | 0.0488 | 0.2565 | 0.7533 |
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+ | No log | 14.96 | 45 | 3.2134 | 0.185 | 0.8700 | 6.7894 | 0.185 | 0.0488 | 0.2630 | 0.7533 |
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+ | No log | 15.96 | 48 | 3.2091 | 0.185 | 0.8691 | 6.7672 | 0.185 | 0.0488 | 0.2585 | 0.7500 |
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+ | No log | 16.96 | 51 | 3.2069 | 0.185 | 0.8687 | 6.6512 | 0.185 | 0.0488 | 0.2536 | 0.7466 |
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+ | No log | 17.96 | 54 | 3.2063 | 0.185 | 0.8682 | 6.5227 | 0.185 | 0.0488 | 0.2520 | 0.7429 |
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+ | No log | 18.96 | 57 | 3.2057 | 0.185 | 0.8682 | 6.5119 | 0.185 | 0.0488 | 0.2514 | 0.7406 |
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+ | No log | 19.96 | 60 | 3.2036 | 0.185 | 0.8678 | 6.5674 | 0.185 | 0.0488 | 0.2501 | 0.7385 |
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+ | No log | 20.96 | 63 | 3.2023 | 0.185 | 0.8677 | 6.5709 | 0.185 | 0.0488 | 0.2506 | 0.7385 |
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+ | No log | 21.96 | 66 | 3.2010 | 0.185 | 0.8675 | 6.5731 | 0.185 | 0.0488 | 0.2631 | 0.7376 |
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+ | No log | 22.96 | 69 | 3.2000 | 0.185 | 0.8673 | 6.5723 | 0.185 | 0.0488 | 0.2591 | 0.7371 |
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+ | No log | 23.96 | 72 | 3.1996 | 0.185 | 0.8673 | 6.5715 | 0.185 | 0.0488 | 0.2593 | 0.7368 |
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+ | No log | 24.96 | 75 | 3.1993 | 0.185 | 0.8672 | 6.5703 | 0.185 | 0.0488 | 0.2594 | 0.7367 |
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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