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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-tiny_tobacco3482_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-tiny_tobacco3482_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: 0.9983 |
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- Accuracy: 0.18 |
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- Brier Loss: 0.8965 |
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- Nll: 6.7849 |
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- F1 Micro: 0.18 |
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- F1 Macro: 0.0305 |
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- Ece: 0.2195 |
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- Aurc: 0.8182 |
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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 | 1.0062 | 0.18 | 0.8980 | 6.1518 | 0.18 | 0.0309 | 0.2213 | 0.7838 | |
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| No log | 1.96 | 24 | 1.0034 | 0.18 | 0.8987 | 5.7795 | 0.18 | 0.0305 | 0.2273 | 0.8165 | |
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| No log | 2.96 | 36 | 1.0025 | 0.18 | 0.8984 | 6.4819 | 0.18 | 0.0305 | 0.2249 | 0.8306 | |
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| No log | 3.96 | 48 | 1.0018 | 0.18 | 0.8982 | 6.8521 | 0.18 | 0.0306 | 0.2205 | 0.8505 | |
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| No log | 4.96 | 60 | 1.0015 | 0.16 | 0.8980 | 6.6853 | 0.16 | 0.0324 | 0.2089 | 0.8798 | |
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| No log | 5.96 | 72 | 1.0011 | 0.175 | 0.8979 | 6.8349 | 0.175 | 0.0314 | 0.2134 | 0.8345 | |
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| No log | 6.96 | 84 | 1.0008 | 0.18 | 0.8976 | 6.8293 | 0.18 | 0.0313 | 0.2249 | 0.8208 | |
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| No log | 7.96 | 96 | 1.0005 | 0.18 | 0.8975 | 6.9400 | 0.18 | 0.0305 | 0.2230 | 0.8140 | |
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| No log | 8.96 | 108 | 1.0003 | 0.18 | 0.8974 | 6.5877 | 0.18 | 0.0306 | 0.2230 | 0.8246 | |
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| No log | 9.96 | 120 | 1.0000 | 0.18 | 0.8973 | 6.5454 | 0.18 | 0.0306 | 0.2188 | 0.8188 | |
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| No log | 10.96 | 132 | 0.9998 | 0.18 | 0.8972 | 6.5555 | 0.18 | 0.0306 | 0.2274 | 0.8151 | |
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| No log | 11.96 | 144 | 0.9996 | 0.18 | 0.8971 | 6.5819 | 0.18 | 0.0306 | 0.2254 | 0.8131 | |
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| No log | 12.96 | 156 | 0.9994 | 0.18 | 0.8970 | 6.7150 | 0.18 | 0.0305 | 0.2255 | 0.8162 | |
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| No log | 13.96 | 168 | 0.9993 | 0.18 | 0.8969 | 6.6542 | 0.18 | 0.0305 | 0.2213 | 0.8220 | |
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| No log | 14.96 | 180 | 0.9991 | 0.18 | 0.8968 | 6.6025 | 0.18 | 0.0305 | 0.2213 | 0.8125 | |
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| No log | 15.96 | 192 | 0.9990 | 0.18 | 0.8968 | 7.0424 | 0.18 | 0.0305 | 0.2301 | 0.8201 | |
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| No log | 16.96 | 204 | 0.9988 | 0.18 | 0.8967 | 6.6676 | 0.18 | 0.0305 | 0.2258 | 0.8153 | |
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| No log | 17.96 | 216 | 0.9987 | 0.18 | 0.8967 | 6.6621 | 0.18 | 0.0305 | 0.2270 | 0.8145 | |
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| No log | 18.96 | 228 | 0.9986 | 0.18 | 0.8967 | 7.0058 | 0.18 | 0.0305 | 0.2259 | 0.8214 | |
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| No log | 19.96 | 240 | 0.9985 | 0.18 | 0.8966 | 6.8777 | 0.18 | 0.0305 | 0.2194 | 0.8183 | |
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| No log | 20.96 | 252 | 0.9984 | 0.18 | 0.8966 | 6.7612 | 0.18 | 0.0305 | 0.2282 | 0.8131 | |
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| No log | 21.96 | 264 | 0.9984 | 0.18 | 0.8966 | 6.7811 | 0.18 | 0.0305 | 0.2282 | 0.8145 | |
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| No log | 22.96 | 276 | 0.9983 | 0.18 | 0.8965 | 6.7044 | 0.18 | 0.0305 | 0.2239 | 0.8167 | |
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| No log | 23.96 | 288 | 0.9983 | 0.18 | 0.8965 | 6.7813 | 0.18 | 0.0305 | 0.2217 | 0.8183 | |
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| No log | 24.96 | 300 | 0.9983 | 0.18 | 0.8965 | 6.7849 | 0.18 | 0.0305 | 0.2195 | 0.8182 | |
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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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