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indic-bert-finetuned-ours-DS

Text Classification
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PyTorch
Safetensors
albert
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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0941
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- - Accuracy: 0.275
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- - Precision: 0.3056
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- - Recall: 0.3467
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- - F1: 0.1803
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  ## Model description
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@@ -42,7 +42,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-07
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  - train_batch_size: 16
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  - eval_batch_size: 32
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  - seed: 43
@@ -54,31 +54,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 1.0988 | 0.99 | 99 | 1.0984 | 0.3 | 0.3611 | 0.3661 | 0.2750 |
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- | 1.0981 | 1.98 | 198 | 1.0980 | 0.29 | 0.2713 | 0.3568 | 0.1997 |
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- | 1.0981 | 2.97 | 297 | 1.0977 | 0.315 | 0.3029 | 0.3736 | 0.2259 |
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- | 1.0976 | 3.96 | 396 | 1.0974 | 0.3 | 0.2816 | 0.3601 | 0.2122 |
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- | 1.0976 | 4.95 | 495 | 1.0971 | 0.295 | 0.2780 | 0.3601 | 0.2041 |
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- | 1.097 | 5.94 | 594 | 1.0968 | 0.29 | 0.2680 | 0.3533 | 0.2012 |
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- | 1.0962 | 6.93 | 693 | 1.0965 | 0.3 | 0.2816 | 0.3601 | 0.2122 |
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- | 1.0963 | 7.92 | 792 | 1.0963 | 0.29 | 0.2761 | 0.3533 | 0.2012 |
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- | 1.0969 | 8.91 | 891 | 1.0961 | 0.3 | 0.2895 | 0.3601 | 0.2122 |
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- | 1.0958 | 9.9 | 990 | 1.0958 | 0.3 | 0.2895 | 0.3601 | 0.2122 |
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- | 1.0959 | 10.89 | 1089 | 1.0956 | 0.3 | 0.2983 | 0.3601 | 0.2122 |
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- | 1.0953 | 11.88 | 1188 | 1.0954 | 0.3 | 0.2983 | 0.3601 | 0.2122 |
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- | 1.0955 | 12.87 | 1287 | 1.0952 | 0.295 | 0.3019 | 0.3567 | 0.2067 |
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- | 1.0948 | 13.86 | 1386 | 1.0951 | 0.295 | 0.3083 | 0.3601 | 0.2040 |
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- | 1.095 | 14.85 | 1485 | 1.0949 | 0.29 | 0.3013 | 0.3568 | 0.1983 |
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- | 1.0951 | 15.84 | 1584 | 1.0948 | 0.29 | 0.3013 | 0.3568 | 0.1983 |
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- | 1.0948 | 16.83 | 1683 | 1.0946 | 0.29 | 0.3143 | 0.3568 | 0.1982 |
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- | 1.0942 | 17.82 | 1782 | 1.0945 | 0.29 | 0.3291 | 0.3568 | 0.1982 |
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- | 1.0949 | 18.81 | 1881 | 1.0944 | 0.28 | 0.3145 | 0.3500 | 0.1863 |
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- | 1.095 | 19.8 | 1980 | 1.0943 | 0.275 | 0.3056 | 0.3467 | 0.1803 |
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- | 1.0945 | 20.79 | 2079 | 1.0943 | 0.275 | 0.3056 | 0.3467 | 0.1803 |
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- | 1.0942 | 21.78 | 2178 | 1.0942 | 0.275 | 0.3056 | 0.3467 | 0.1803 |
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- | 1.0938 | 22.77 | 2277 | 1.0942 | 0.275 | 0.3056 | 0.3467 | 0.1803 |
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- | 1.0953 | 23.76 | 2376 | 1.0941 | 0.275 | 0.3056 | 0.3467 | 0.1803 |
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- | 1.0943 | 24.75 | 2475 | 1.0941 | 0.275 | 0.3056 | 0.3467 | 0.1803 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [ai4bharat/indic-bert](https://huggingface.co/ai4bharat/indic-bert) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.1832
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+ - Accuracy: 0.655
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+ - Precision: 0.6023
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+ - Recall: 0.6027
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+ - F1: 0.6025
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 32
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  - seed: 43
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.0681 | 0.99 | 99 | 1.0180 | 0.365 | 0.3435 | 0.4038 | 0.2773 |
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+ | 0.9384 | 1.98 | 198 | 0.8475 | 0.62 | 0.6235 | 0.5610 | 0.4821 |
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+ | 0.8201 | 2.97 | 297 | 0.8187 | 0.68 | 0.6839 | 0.6086 | 0.5812 |
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+ | 0.7178 | 3.96 | 396 | 0.7717 | 0.7 | 0.7117 | 0.6670 | 0.6470 |
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+ | 0.62 | 4.95 | 495 | 0.7839 | 0.66 | 0.6165 | 0.6244 | 0.6174 |
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+ | 0.5135 | 5.94 | 594 | 0.8392 | 0.675 | 0.6270 | 0.6234 | 0.6246 |
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+ | 0.4073 | 6.93 | 693 | 0.8930 | 0.665 | 0.6251 | 0.6254 | 0.6240 |
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+ | 0.3365 | 7.92 | 792 | 0.9362 | 0.675 | 0.6298 | 0.6276 | 0.6242 |
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+ | 0.2719 | 8.91 | 891 | 1.0108 | 0.685 | 0.6388 | 0.6293 | 0.6326 |
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+ | 0.2007 | 9.9 | 990 | 1.1214 | 0.675 | 0.6300 | 0.6299 | 0.6290 |
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+ | 0.1567 | 10.89 | 1089 | 1.1367 | 0.67 | 0.6193 | 0.6212 | 0.6178 |
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+ | 0.1074 | 11.88 | 1188 | 1.3157 | 0.65 | 0.6292 | 0.6317 | 0.6227 |
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+ | 0.0821 | 12.87 | 1287 | 1.5412 | 0.665 | 0.6415 | 0.6330 | 0.6259 |
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+ | 0.0588 | 13.86 | 1386 | 1.7215 | 0.64 | 0.5862 | 0.5869 | 0.5865 |
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+ | 0.0337 | 14.85 | 1485 | 1.7556 | 0.64 | 0.6078 | 0.6082 | 0.6032 |
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+ | 0.0244 | 15.84 | 1584 | 1.8713 | 0.66 | 0.6173 | 0.6186 | 0.6158 |
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+ | 0.0166 | 16.83 | 1683 | 1.9666 | 0.66 | 0.5995 | 0.5973 | 0.5973 |
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+ | 0.0124 | 17.82 | 1782 | 1.9245 | 0.66 | 0.6165 | 0.6194 | 0.6163 |
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+ | 0.0079 | 18.81 | 1881 | 2.0814 | 0.65 | 0.6026 | 0.6023 | 0.6012 |
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+ | 0.0051 | 19.8 | 1980 | 2.1029 | 0.645 | 0.6014 | 0.5986 | 0.5975 |
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+ | 0.0031 | 20.79 | 2079 | 2.1155 | 0.655 | 0.6029 | 0.6027 | 0.6023 |
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+ | 0.0029 | 21.78 | 2178 | 2.1221 | 0.655 | 0.6 | 0.6000 | 0.5999 |
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+ | 0.0021 | 22.77 | 2277 | 2.2065 | 0.65 | 0.5917 | 0.5898 | 0.5905 |
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+ | 0.0017 | 23.76 | 2376 | 2.1903 | 0.65 | 0.5910 | 0.5898 | 0.5902 |
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+ | 0.0016 | 24.75 | 2475 | 2.1832 | 0.655 | 0.6023 | 0.6027 | 0.6025 |
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  ### Framework versions