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distilbert-base-uncased-name-classifier

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distilbert-base-uncased-name-classifier

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  1. README.md +19 -19
  2. model.safetensors +1 -1
  3. runs/Dec07_19-32-58_elesage-pc/events.out.tfevents.1765154092.elesage-pc.198534.0 +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 [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0230
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- - Accuracy: 0.9937
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- - Precision: 0.9983
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- - Recall: 0.9904
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- - F1: 0.9943
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  ## Model description
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@@ -51,25 +51,25 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 1000
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- - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.0397 | 0.0718 | 2000 | 0.0405 | 0.9885 | 0.9981 | 0.9812 | 0.9896 |
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- | 0.0324 | 0.1435 | 4000 | 0.0303 | 0.9914 | 0.9970 | 0.9875 | 0.9923 |
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- | 0.031 | 0.2153 | 6000 | 0.0295 | 0.9914 | 0.9938 | 0.9907 | 0.9923 |
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- | 0.0295 | 0.2870 | 8000 | 0.0271 | 0.9924 | 0.9970 | 0.9894 | 0.9932 |
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- | 0.0275 | 0.3588 | 10000 | 0.0262 | 0.9926 | 0.9964 | 0.9904 | 0.9934 |
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- | 0.0281 | 0.4305 | 12000 | 0.0256 | 0.9930 | 0.9981 | 0.9893 | 0.9937 |
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- | 0.0244 | 0.5023 | 14000 | 0.0272 | 0.9926 | 0.9991 | 0.9876 | 0.9933 |
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- | 0.0229 | 0.5740 | 16000 | 0.0254 | 0.9931 | 0.9970 | 0.9907 | 0.9938 |
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- | 0.0264 | 0.6458 | 18000 | 0.0248 | 0.9932 | 0.9986 | 0.9892 | 0.9939 |
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- | 0.0258 | 0.7175 | 20000 | 0.0237 | 0.9934 | 0.9983 | 0.9899 | 0.9941 |
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- | 0.0236 | 0.7893 | 22000 | 0.0234 | 0.9936 | 0.9982 | 0.9903 | 0.9943 |
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- | 0.0253 | 0.8610 | 24000 | 0.0231 | 0.9936 | 0.9979 | 0.9907 | 0.9943 |
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- | 0.0248 | 0.9328 | 26000 | 0.0230 | 0.9937 | 0.9983 | 0.9904 | 0.9943 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0225
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+ - Accuracy: 0.9939
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+ - Precision: 0.9979
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+ - Recall: 0.9912
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+ - F1: 0.9945
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.0323 | 0.1435 | 4000 | 0.0303 | 0.9915 | 0.9975 | 0.9872 | 0.9923 |
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+ | 0.0297 | 0.2870 | 8000 | 0.0279 | 0.9923 | 0.9963 | 0.9899 | 0.9931 |
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+ | 0.0283 | 0.4305 | 12000 | 0.0257 | 0.9929 | 0.9978 | 0.9895 | 0.9936 |
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+ | 0.0229 | 0.5740 | 16000 | 0.0258 | 0.9932 | 0.9972 | 0.9905 | 0.9938 |
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+ | 0.0263 | 0.7175 | 20000 | 0.0239 | 0.9934 | 0.9981 | 0.9901 | 0.9940 |
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+ | 0.0256 | 0.8610 | 24000 | 0.0233 | 0.9935 | 0.9976 | 0.9908 | 0.9942 |
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+ | 0.023 | 1.0046 | 28000 | 0.0233 | 0.9936 | 0.9976 | 0.9909 | 0.9943 |
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+ | 0.0214 | 1.1481 | 32000 | 0.0231 | 0.9937 | 0.9986 | 0.9902 | 0.9944 |
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+ | 0.0207 | 1.2916 | 36000 | 0.0232 | 0.9938 | 0.9984 | 0.9905 | 0.9944 |
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+ | 0.0215 | 1.4351 | 40000 | 0.0229 | 0.9938 | 0.9978 | 0.9910 | 0.9944 |
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+ | 0.0206 | 1.5786 | 44000 | 0.0232 | 0.9938 | 0.9976 | 0.9913 | 0.9944 |
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+ | 0.0197 | 1.7221 | 48000 | 0.0229 | 0.9939 | 0.9978 | 0.9912 | 0.9945 |
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+ | 0.0216 | 1.8656 | 52000 | 0.0225 | 0.9939 | 0.9979 | 0.9912 | 0.9945 |
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  ### Framework versions
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