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doc-topic-model_eval-00_train-03

Text Classification
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Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
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avsolatorio/doc-topic-model_eval-00_train-03

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  1. README.md +21 -21
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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  library_name: transformers
 
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  base_model: microsoft/deberta-v3-small
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  tags:
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  - generated_from_trainer
@@ -20,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0375
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  - Accuracy: 0.9878
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- - F1: 0.6375
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- - Precision: 0.7079
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- - Recall: 0.5798
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  ## Model description
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@@ -56,23 +57,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.0923 | 0.4931 | 1000 | 0.0865 | 0.9815 | 0.0 | 0.0 | 0.0 |
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- | 0.0734 | 0.9862 | 2000 | 0.0668 | 0.9815 | 0.0 | 0.0 | 0.0 |
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- | 0.0606 | 1.4793 | 3000 | 0.0552 | 0.9824 | 0.1265 | 0.7701 | 0.0689 |
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- | 0.0532 | 1.9724 | 4000 | 0.0491 | 0.9841 | 0.2944 | 0.8178 | 0.1795 |
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- | 0.0466 | 2.4655 | 5000 | 0.0467 | 0.9851 | 0.4323 | 0.7342 | 0.3063 |
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- | 0.0433 | 2.9586 | 6000 | 0.0428 | 0.9859 | 0.4847 | 0.7565 | 0.3566 |
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- | 0.0391 | 3.4517 | 7000 | 0.0408 | 0.9866 | 0.5389 | 0.7450 | 0.4221 |
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- | 0.0378 | 3.9448 | 8000 | 0.0395 | 0.9867 | 0.5527 | 0.7365 | 0.4423 |
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- | 0.0338 | 4.4379 | 9000 | 0.0387 | 0.9870 | 0.5844 | 0.7160 | 0.4936 |
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- | 0.0333 | 4.9310 | 10000 | 0.0380 | 0.9871 | 0.5953 | 0.7094 | 0.5128 |
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- | 0.0301 | 5.4241 | 11000 | 0.0371 | 0.9876 | 0.6042 | 0.7368 | 0.5120 |
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- | 0.0292 | 5.9172 | 12000 | 0.0367 | 0.9877 | 0.6120 | 0.7381 | 0.5227 |
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- | 0.0266 | 6.4103 | 13000 | 0.0369 | 0.9879 | 0.6132 | 0.7535 | 0.5170 |
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- | 0.0257 | 6.9034 | 14000 | 0.0371 | 0.9877 | 0.6187 | 0.7257 | 0.5392 |
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- | 0.0229 | 7.3964 | 15000 | 0.0371 | 0.9880 | 0.6330 | 0.7279 | 0.5600 |
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- | 0.0238 | 7.8895 | 16000 | 0.0372 | 0.9879 | 0.6306 | 0.7250 | 0.5579 |
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- | 0.0198 | 8.3826 | 17000 | 0.0375 | 0.9878 | 0.6375 | 0.7079 | 0.5798 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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+ license: mit
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  base_model: microsoft/deberta-v3-small
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  tags:
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  - generated_from_trainer
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0381
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  - Accuracy: 0.9878
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+ - F1: 0.6228
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+ - Precision: 0.7288
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+ - Recall: 0.5437
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.0935 | 0.4931 | 1000 | 0.0895 | 0.9815 | 0.0 | 0.0 | 0.0 |
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+ | 0.0764 | 0.9862 | 2000 | 0.0700 | 0.9815 | 0.0 | 0.0 | 0.0 |
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+ | 0.0621 | 1.4793 | 3000 | 0.0567 | 0.9821 | 0.0730 | 0.8925 | 0.0381 |
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+ | 0.0542 | 1.9724 | 4000 | 0.0497 | 0.9841 | 0.2891 | 0.8391 | 0.1747 |
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+ | 0.0468 | 2.4655 | 5000 | 0.0465 | 0.9853 | 0.4216 | 0.7739 | 0.2897 |
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+ | 0.0441 | 2.9586 | 6000 | 0.0435 | 0.9861 | 0.4879 | 0.7667 | 0.3578 |
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+ | 0.0395 | 3.4517 | 7000 | 0.0417 | 0.9862 | 0.5322 | 0.7197 | 0.4222 |
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+ | 0.0384 | 3.9448 | 8000 | 0.0401 | 0.9866 | 0.5600 | 0.7182 | 0.4589 |
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+ | 0.0343 | 4.4379 | 9000 | 0.0393 | 0.9870 | 0.5789 | 0.7217 | 0.4833 |
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+ | 0.0337 | 4.9310 | 10000 | 0.0378 | 0.9873 | 0.5907 | 0.7358 | 0.4934 |
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+ | 0.0305 | 5.4241 | 11000 | 0.0375 | 0.9875 | 0.5960 | 0.7457 | 0.4963 |
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+ | 0.0295 | 5.9172 | 12000 | 0.0378 | 0.9874 | 0.6050 | 0.7213 | 0.5210 |
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+ | 0.0271 | 6.4103 | 13000 | 0.0376 | 0.9877 | 0.6048 | 0.7457 | 0.5087 |
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+ | 0.0257 | 6.9034 | 14000 | 0.0379 | 0.9875 | 0.6068 | 0.7269 | 0.5208 |
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+ | 0.0234 | 7.3964 | 15000 | 0.0377 | 0.9876 | 0.6246 | 0.7108 | 0.5571 |
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+ | 0.0241 | 7.8895 | 16000 | 0.0381 | 0.9878 | 0.6228 | 0.7288 | 0.5437 |
 
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  ### Framework versions
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