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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_rvl_cdip_100_examples_per_class_simkd_CEKD_t1_aNone |
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results: [] |
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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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# dit-small_rvl_cdip_100_examples_per_class_simkd_CEKD_t1_aNone |
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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: 0.1481 |
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- Accuracy: 0.08 |
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- Brier Loss: 0.9369 |
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- Nll: 9.2883 |
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- F1 Micro: 0.08 |
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- F1 Macro: 0.0357 |
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- Ece: 0.1153 |
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- Aurc: 0.8531 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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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: 25 |
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### Training results |
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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 | 12 | 0.1528 | 0.0625 | 0.9377 | 9.9656 | 0.0625 | 0.0074 | 0.1025 | 0.9319 | |
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| No log | 1.96 | 24 | 0.1507 | 0.06 | 0.9377 | 9.9434 | 0.06 | 0.0074 | 0.1036 | 0.9537 | |
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| No log | 2.96 | 36 | 0.1500 | 0.0625 | 0.9376 | 8.6216 | 0.0625 | 0.0074 | 0.1019 | 0.9383 | |
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| No log | 3.96 | 48 | 0.1498 | 0.0625 | 0.9376 | 9.2776 | 0.0625 | 0.0074 | 0.1032 | 0.9438 | |
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| No log | 4.96 | 60 | 0.1496 | 0.0625 | 0.9375 | 9.3105 | 0.0625 | 0.0074 | 0.1017 | 0.9421 | |
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| No log | 5.96 | 72 | 0.1495 | 0.0625 | 0.9375 | 9.7276 | 0.0625 | 0.0074 | 0.1029 | 0.9380 | |
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| No log | 6.96 | 84 | 0.1494 | 0.0625 | 0.9374 | 9.6348 | 0.0625 | 0.0074 | 0.1017 | 0.9347 | |
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| No log | 7.96 | 96 | 0.1493 | 0.0625 | 0.9374 | 9.6145 | 0.0625 | 0.0074 | 0.1008 | 0.9359 | |
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| No log | 8.96 | 108 | 0.1492 | 0.0625 | 0.9374 | 9.5748 | 0.0625 | 0.0074 | 0.1019 | 0.9371 | |
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| No log | 9.96 | 120 | 0.1491 | 0.0625 | 0.9373 | 9.5551 | 0.0625 | 0.0074 | 0.1005 | 0.9372 | |
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| No log | 10.96 | 132 | 0.1490 | 0.065 | 0.9373 | 9.5267 | 0.065 | 0.0122 | 0.1047 | 0.9315 | |
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| No log | 11.96 | 144 | 0.1489 | 0.065 | 0.9373 | 9.5165 | 0.065 | 0.0122 | 0.1043 | 0.9284 | |
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| No log | 12.96 | 156 | 0.1488 | 0.065 | 0.9372 | 9.5162 | 0.065 | 0.0123 | 0.1068 | 0.9302 | |
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| No log | 13.96 | 168 | 0.1488 | 0.07 | 0.9372 | 9.5139 | 0.07 | 0.0213 | 0.1070 | 0.9275 | |
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| No log | 14.96 | 180 | 0.1487 | 0.0725 | 0.9371 | 9.4579 | 0.0725 | 0.0253 | 0.1095 | 0.9174 | |
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| No log | 15.96 | 192 | 0.1486 | 0.075 | 0.9371 | 9.3950 | 0.075 | 0.0286 | 0.1106 | 0.9161 | |
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| No log | 16.96 | 204 | 0.1485 | 0.075 | 0.9371 | 9.3347 | 0.075 | 0.0280 | 0.1055 | 0.9014 | |
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| No log | 17.96 | 216 | 0.1484 | 0.0775 | 0.9370 | 9.3157 | 0.0775 | 0.0315 | 0.1089 | 0.8695 | |
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| No log | 18.96 | 228 | 0.1483 | 0.08 | 0.9370 | 9.3125 | 0.08 | 0.0362 | 0.1133 | 0.8526 | |
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| No log | 19.96 | 240 | 0.1483 | 0.08 | 0.9370 | 9.2915 | 0.08 | 0.0360 | 0.1113 | 0.8554 | |
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| No log | 20.96 | 252 | 0.1482 | 0.0775 | 0.9370 | 9.2937 | 0.0775 | 0.0374 | 0.1118 | 0.8475 | |
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| No log | 21.96 | 264 | 0.1482 | 0.08 | 0.9369 | 9.2903 | 0.08 | 0.0357 | 0.1167 | 0.8526 | |
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| No log | 22.96 | 276 | 0.1482 | 0.08 | 0.9369 | 9.2888 | 0.08 | 0.0357 | 0.1099 | 0.8540 | |
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| No log | 23.96 | 288 | 0.1481 | 0.08 | 0.9369 | 9.2877 | 0.08 | 0.0357 | 0.1126 | 0.8531 | |
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| No log | 24.96 | 300 | 0.1481 | 0.08 | 0.9369 | 9.2883 | 0.08 | 0.0357 | 0.1153 | 0.8531 | |
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### Framework versions |
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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 |
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