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mdeberta-v3-base-name-classifier-v2

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ele-sage/mdeberta-v3-base-name-classifier-v2

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  1. README.md +31 -31
  2. model.safetensors +1 -1
  3. runs/Dec07_16-45-13_elesage-pc/events.out.tfevents.1765144003.elesage-pc.128861.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +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/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0216
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- - Accuracy: 0.9942
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- - Precision: 0.9983
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  - Recall: 0.9913
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- - F1: 0.9948
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  ## Model description
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@@ -57,33 +57,33 @@ 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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- | 0.047 | 0.0359 | 2000 | 0.0390 | 0.9903 | 0.9974 | 0.9851 | 0.9912 |
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- | 0.0322 | 0.0718 | 4000 | 0.0346 | 0.9921 | 0.9968 | 0.9890 | 0.9929 |
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- | 0.0325 | 0.1076 | 6000 | 0.0293 | 0.9924 | 0.9970 | 0.9893 | 0.9932 |
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- | 0.0342 | 0.1435 | 8000 | 0.0264 | 0.9927 | 0.9973 | 0.9895 | 0.9934 |
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- | 0.0301 | 0.1794 | 10000 | 0.0260 | 0.9929 | 0.9967 | 0.9905 | 0.9936 |
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- | 0.0291 | 0.2153 | 12000 | 0.0259 | 0.9931 | 0.9984 | 0.9893 | 0.9938 |
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- | 0.0246 | 0.2511 | 14000 | 0.0263 | 0.9931 | 0.9971 | 0.9905 | 0.9938 |
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- | 0.0321 | 0.2870 | 16000 | 0.0264 | 0.9934 | 0.9988 | 0.9893 | 0.9940 |
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- | 0.0256 | 0.3229 | 18000 | 0.0250 | 0.9935 | 0.9980 | 0.9903 | 0.9941 |
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- | 0.0234 | 0.3588 | 20000 | 0.0260 | 0.9934 | 0.9969 | 0.9912 | 0.9940 |
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- | 0.0246 | 0.3946 | 22000 | 0.0246 | 0.9935 | 0.9975 | 0.9909 | 0.9942 |
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- | 0.0238 | 0.4305 | 24000 | 0.0252 | 0.9932 | 0.9961 | 0.9917 | 0.9938 |
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- | 0.0263 | 0.4664 | 26000 | 0.0238 | 0.9936 | 0.9976 | 0.9910 | 0.9943 |
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- | 0.0234 | 0.5023 | 28000 | 0.0250 | 0.9936 | 0.9972 | 0.9913 | 0.9943 |
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- | 0.0241 | 0.5382 | 30000 | 0.0230 | 0.9939 | 0.9978 | 0.9912 | 0.9945 |
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- | 0.0238 | 0.5740 | 32000 | 0.0228 | 0.9939 | 0.9984 | 0.9907 | 0.9945 |
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- | 0.0243 | 0.6099 | 34000 | 0.0239 | 0.9939 | 0.9993 | 0.9897 | 0.9945 |
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- | 0.023 | 0.6458 | 36000 | 0.0228 | 0.9939 | 0.9980 | 0.9911 | 0.9945 |
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- | 0.0252 | 0.6817 | 38000 | 0.0230 | 0.9941 | 0.9987 | 0.9907 | 0.9947 |
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- | 0.0251 | 0.7175 | 40000 | 0.0223 | 0.9940 | 0.9977 | 0.9915 | 0.9946 |
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- | 0.0217 | 0.7534 | 42000 | 0.0226 | 0.9940 | 0.9976 | 0.9916 | 0.9946 |
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- | 0.0269 | 0.7893 | 44000 | 0.0220 | 0.9941 | 0.9981 | 0.9914 | 0.9947 |
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- | 0.0227 | 0.8252 | 46000 | 0.0224 | 0.9939 | 0.9972 | 0.9918 | 0.9945 |
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- | 0.026 | 0.8610 | 48000 | 0.0216 | 0.9942 | 0.9986 | 0.9911 | 0.9948 |
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- | 0.0213 | 0.8969 | 50000 | 0.0220 | 0.9942 | 0.9983 | 0.9913 | 0.9948 |
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- | 0.0233 | 0.9328 | 52000 | 0.0217 | 0.9942 | 0.9982 | 0.9913 | 0.9948 |
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- | 0.0239 | 0.9687 | 54000 | 0.0216 | 0.9942 | 0.9983 | 0.9913 | 0.9948 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0215
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+ - Accuracy: 0.9943
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+ - Precision: 0.9984
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  - Recall: 0.9913
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+ - F1: 0.9949
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.0459 | 0.0359 | 2000 | 0.0425 | 0.9894 | 0.9981 | 0.9830 | 0.9905 |
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+ | 0.032 | 0.0718 | 4000 | 0.0343 | 0.9919 | 0.9960 | 0.9895 | 0.9927 |
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+ | 0.0322 | 0.1076 | 6000 | 0.0302 | 0.9926 | 0.9975 | 0.9893 | 0.9933 |
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+ | 0.0347 | 0.1435 | 8000 | 0.0262 | 0.9928 | 0.9968 | 0.9903 | 0.9936 |
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+ | 0.0292 | 0.1794 | 10000 | 0.0260 | 0.9931 | 0.9973 | 0.9903 | 0.9938 |
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+ | 0.029 | 0.2153 | 12000 | 0.0251 | 0.9933 | 0.9974 | 0.9905 | 0.9940 |
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+ | 0.0243 | 0.2511 | 14000 | 0.0254 | 0.9933 | 0.9975 | 0.9905 | 0.9940 |
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+ | 0.0309 | 0.2870 | 16000 | 0.0255 | 0.9935 | 0.9986 | 0.9898 | 0.9941 |
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+ | 0.0247 | 0.3229 | 18000 | 0.0242 | 0.9937 | 0.9983 | 0.9903 | 0.9943 |
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+ | 0.0232 | 0.3588 | 20000 | 0.0256 | 0.9935 | 0.9976 | 0.9908 | 0.9942 |
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+ | 0.0243 | 0.3946 | 22000 | 0.0238 | 0.9937 | 0.9979 | 0.9907 | 0.9943 |
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+ | 0.0235 | 0.4305 | 24000 | 0.0246 | 0.9935 | 0.9969 | 0.9914 | 0.9941 |
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+ | 0.0267 | 0.4664 | 26000 | 0.0235 | 0.9937 | 0.9975 | 0.9912 | 0.9943 |
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+ | 0.0228 | 0.5023 | 28000 | 0.0246 | 0.9937 | 0.9977 | 0.9910 | 0.9943 |
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+ | 0.025 | 0.5382 | 30000 | 0.0226 | 0.9938 | 0.9978 | 0.9912 | 0.9945 |
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+ | 0.0229 | 0.5740 | 32000 | 0.0229 | 0.9939 | 0.9982 | 0.9909 | 0.9945 |
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+ | 0.0234 | 0.6099 | 34000 | 0.0237 | 0.9940 | 0.9991 | 0.9900 | 0.9946 |
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+ | 0.0232 | 0.6458 | 36000 | 0.0230 | 0.9939 | 0.9975 | 0.9915 | 0.9945 |
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+ | 0.0257 | 0.6817 | 38000 | 0.0228 | 0.9942 | 0.9988 | 0.9907 | 0.9947 |
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+ | 0.0254 | 0.7175 | 40000 | 0.0221 | 0.9940 | 0.9979 | 0.9914 | 0.9946 |
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+ | 0.0222 | 0.7534 | 42000 | 0.0223 | 0.9941 | 0.9979 | 0.9915 | 0.9947 |
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+ | 0.0271 | 0.7893 | 44000 | 0.0219 | 0.9942 | 0.9981 | 0.9914 | 0.9948 |
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+ | 0.0231 | 0.8252 | 46000 | 0.0222 | 0.9940 | 0.9975 | 0.9917 | 0.9946 |
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+ | 0.0258 | 0.8610 | 48000 | 0.0214 | 0.9943 | 0.9986 | 0.9912 | 0.9949 |
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+ | 0.0217 | 0.8969 | 50000 | 0.0219 | 0.9943 | 0.9983 | 0.9914 | 0.9949 |
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+ | 0.0234 | 0.9328 | 52000 | 0.0215 | 0.9943 | 0.9983 | 0.9914 | 0.9948 |
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+ | 0.0237 | 0.9687 | 54000 | 0.0215 | 0.9943 | 0.9984 | 0.9913 | 0.9949 |
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  ### Framework versions
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