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distilbert-base-uncased-finetuned-ner

Token Classification
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distilbert
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  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.4181
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- - Precision: 0.6106
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- - Recall: 0.6615
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- - F1: 0.635
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- - Accuracy: 0.9189
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  ## Model description
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@@ -49,42 +49,62 @@ The following hyperparameters were used during training:
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  - seed: 42
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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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- - num_epochs: 30
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 23 | 0.3610 | 0.4795 | 0.6094 | 0.5367 | 0.9045 |
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- | No log | 2.0 | 46 | 0.3516 | 0.5330 | 0.5885 | 0.5594 | 0.9141 |
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- | No log | 3.0 | 69 | 0.3591 | 0.5346 | 0.6042 | 0.5672 | 0.9147 |
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- | No log | 4.0 | 92 | 0.3602 | 0.5226 | 0.6615 | 0.5839 | 0.9129 |
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- | No log | 5.0 | 115 | 0.3706 | 0.5315 | 0.6146 | 0.5700 | 0.9123 |
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- | No log | 6.0 | 138 | 0.3652 | 0.5631 | 0.6042 | 0.5829 | 0.9165 |
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- | No log | 7.0 | 161 | 0.3618 | 0.5640 | 0.6198 | 0.5906 | 0.9153 |
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- | No log | 8.0 | 184 | 0.3680 | 0.5755 | 0.6354 | 0.6040 | 0.9165 |
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- | No log | 9.0 | 207 | 0.3782 | 0.5789 | 0.6302 | 0.6035 | 0.9183 |
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- | No log | 10.0 | 230 | 0.3926 | 0.6020 | 0.6302 | 0.6158 | 0.9189 |
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- | No log | 11.0 | 253 | 0.3816 | 0.5845 | 0.6667 | 0.6229 | 0.9171 |
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- | No log | 12.0 | 276 | 0.3811 | 0.5942 | 0.6406 | 0.6165 | 0.9195 |
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- | No log | 13.0 | 299 | 0.3857 | 0.5885 | 0.6406 | 0.6135 | 0.9189 |
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- | No log | 14.0 | 322 | 0.3966 | 0.5714 | 0.6458 | 0.6064 | 0.9141 |
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- | No log | 15.0 | 345 | 0.3927 | 0.6019 | 0.6615 | 0.6303 | 0.9183 |
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- | No log | 16.0 | 368 | 0.3955 | 0.5907 | 0.6615 | 0.6241 | 0.9165 |
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- | No log | 17.0 | 391 | 0.4124 | 0.5931 | 0.6302 | 0.6111 | 0.9171 |
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- | No log | 18.0 | 414 | 0.4112 | 0.5733 | 0.6719 | 0.6187 | 0.9135 |
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- | No log | 19.0 | 437 | 0.4177 | 0.5829 | 0.6406 | 0.6104 | 0.9159 |
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- | No log | 20.0 | 460 | 0.4100 | 0.6028 | 0.6719 | 0.6355 | 0.9159 |
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- | No log | 21.0 | 483 | 0.4159 | 0.5869 | 0.6510 | 0.6173 | 0.9165 |
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- | 0.0279 | 22.0 | 506 | 0.4100 | 0.5853 | 0.6615 | 0.6210 | 0.9153 |
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- | 0.0279 | 23.0 | 529 | 0.4127 | 0.6172 | 0.6719 | 0.6434 | 0.9189 |
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- | 0.0279 | 24.0 | 552 | 0.4074 | 0.5945 | 0.6719 | 0.6308 | 0.9153 |
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- | 0.0279 | 25.0 | 575 | 0.4056 | 0.5909 | 0.6771 | 0.6311 | 0.9165 |
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- | 0.0279 | 26.0 | 598 | 0.4079 | 0.5740 | 0.6667 | 0.6169 | 0.9153 |
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- | 0.0279 | 27.0 | 621 | 0.4184 | 0.6117 | 0.6562 | 0.6332 | 0.9189 |
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- | 0.0279 | 28.0 | 644 | 0.4177 | 0.6165 | 0.6615 | 0.6382 | 0.9195 |
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- | 0.0279 | 29.0 | 667 | 0.4178 | 0.6106 | 0.6615 | 0.635 | 0.9189 |
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- | 0.0279 | 30.0 | 690 | 0.4181 | 0.6106 | 0.6615 | 0.635 | 0.9189 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.4331
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+ - Precision: 0.7801
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+ - Recall: 0.7129
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+ - F1: 0.745
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+ - Accuracy: 0.9363
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  ## Model description
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  - seed: 42
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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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+ - num_epochs: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 23 | 0.8283 | 0.0 | 0.0 | 0.0 | 0.8332 |
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+ | No log | 2.0 | 46 | 0.5781 | 0.4474 | 0.0813 | 0.1377 | 0.8482 |
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+ | No log | 3.0 | 69 | 0.4927 | 0.4841 | 0.3636 | 0.4153 | 0.8913 |
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+ | No log | 4.0 | 92 | 0.4348 | 0.4657 | 0.4545 | 0.4600 | 0.9044 |
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+ | No log | 5.0 | 115 | 0.4293 | 0.5561 | 0.4976 | 0.5253 | 0.9088 |
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+ | No log | 6.0 | 138 | 0.3934 | 0.6313 | 0.5981 | 0.6143 | 0.9244 |
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+ | No log | 7.0 | 161 | 0.3961 | 0.7219 | 0.6459 | 0.6818 | 0.9313 |
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+ | No log | 8.0 | 184 | 0.3648 | 0.7098 | 0.6555 | 0.6816 | 0.9325 |
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+ | No log | 9.0 | 207 | 0.3961 | 0.7582 | 0.6603 | 0.7059 | 0.9357 |
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+ | No log | 10.0 | 230 | 0.3800 | 0.7474 | 0.6794 | 0.7118 | 0.9350 |
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+ | No log | 11.0 | 253 | 0.3661 | 0.7474 | 0.6794 | 0.7118 | 0.9332 |
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+ | No log | 12.0 | 276 | 0.3697 | 0.7619 | 0.6890 | 0.7236 | 0.9344 |
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+ | No log | 13.0 | 299 | 0.3829 | 0.7660 | 0.6890 | 0.7254 | 0.9350 |
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+ | No log | 14.0 | 322 | 0.3859 | 0.7849 | 0.6986 | 0.7392 | 0.9350 |
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+ | No log | 15.0 | 345 | 0.3760 | 0.7946 | 0.7033 | 0.7462 | 0.9375 |
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+ | No log | 16.0 | 368 | 0.3609 | 0.7602 | 0.7129 | 0.7358 | 0.9357 |
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+ | No log | 17.0 | 391 | 0.3687 | 0.7766 | 0.6986 | 0.7355 | 0.9350 |
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+ | No log | 18.0 | 414 | 0.3856 | 0.8043 | 0.7081 | 0.7532 | 0.9375 |
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+ | No log | 19.0 | 437 | 0.3901 | 0.7861 | 0.7033 | 0.7424 | 0.9369 |
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+ | No log | 20.0 | 460 | 0.4151 | 0.8276 | 0.6890 | 0.7520 | 0.9388 |
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+ | No log | 21.0 | 483 | 0.3892 | 0.7824 | 0.7225 | 0.7512 | 0.9382 |
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+ | 0.1775 | 22.0 | 506 | 0.3952 | 0.7947 | 0.7225 | 0.7569 | 0.9375 |
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+ | 0.1775 | 23.0 | 529 | 0.3906 | 0.7817 | 0.7368 | 0.7586 | 0.9382 |
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+ | 0.1775 | 24.0 | 552 | 0.4132 | 0.8156 | 0.6986 | 0.7526 | 0.9413 |
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+ | 0.1775 | 25.0 | 575 | 0.4048 | 0.7979 | 0.7177 | 0.7557 | 0.9388 |
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+ | 0.1775 | 26.0 | 598 | 0.4026 | 0.7772 | 0.7177 | 0.7463 | 0.9363 |
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+ | 0.1775 | 27.0 | 621 | 0.4084 | 0.7789 | 0.7081 | 0.7419 | 0.9363 |
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+ | 0.1775 | 28.0 | 644 | 0.4081 | 0.7865 | 0.7225 | 0.7531 | 0.9375 |
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+ | 0.1775 | 29.0 | 667 | 0.4058 | 0.7795 | 0.7273 | 0.7525 | 0.9375 |
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+ | 0.1775 | 30.0 | 690 | 0.4100 | 0.7772 | 0.7177 | 0.7463 | 0.9369 |
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+ | 0.1775 | 31.0 | 713 | 0.4146 | 0.7824 | 0.7225 | 0.7512 | 0.9363 |
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+ | 0.1775 | 32.0 | 736 | 0.4142 | 0.7865 | 0.7225 | 0.7531 | 0.9363 |
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+ | 0.1775 | 33.0 | 759 | 0.4168 | 0.7824 | 0.7225 | 0.7512 | 0.9369 |
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+ | 0.1775 | 34.0 | 782 | 0.4367 | 0.8122 | 0.7033 | 0.7538 | 0.9388 |
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+ | 0.1775 | 35.0 | 805 | 0.4282 | 0.7884 | 0.7129 | 0.7487 | 0.9363 |
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+ | 0.1775 | 36.0 | 828 | 0.4249 | 0.7842 | 0.7129 | 0.7469 | 0.9357 |
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+ | 0.1775 | 37.0 | 851 | 0.4297 | 0.7884 | 0.7129 | 0.7487 | 0.9363 |
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+ | 0.1775 | 38.0 | 874 | 0.4218 | 0.7824 | 0.7225 | 0.7512 | 0.9375 |
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+ | 0.1775 | 39.0 | 897 | 0.4267 | 0.7842 | 0.7129 | 0.7469 | 0.9363 |
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+ | 0.1775 | 40.0 | 920 | 0.4272 | 0.7937 | 0.7177 | 0.7538 | 0.9369 |
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+ | 0.1775 | 41.0 | 943 | 0.4308 | 0.7926 | 0.7129 | 0.7506 | 0.9363 |
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+ | 0.1775 | 42.0 | 966 | 0.4390 | 0.7884 | 0.7129 | 0.7487 | 0.9363 |
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+ | 0.1775 | 43.0 | 989 | 0.4366 | 0.7914 | 0.7081 | 0.7475 | 0.9375 |
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+ | 0.0065 | 44.0 | 1012 | 0.4311 | 0.7749 | 0.7081 | 0.74 | 0.9350 |
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+ | 0.0065 | 45.0 | 1035 | 0.4276 | 0.7760 | 0.7129 | 0.7431 | 0.9357 |
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+ | 0.0065 | 46.0 | 1058 | 0.4313 | 0.7801 | 0.7129 | 0.745 | 0.9357 |
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+ | 0.0065 | 47.0 | 1081 | 0.4330 | 0.7801 | 0.7129 | 0.745 | 0.9357 |
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+ | 0.0065 | 48.0 | 1104 | 0.4325 | 0.7801 | 0.7129 | 0.745 | 0.9363 |
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+ | 0.0065 | 49.0 | 1127 | 0.4328 | 0.7801 | 0.7129 | 0.745 | 0.9363 |
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+ | 0.0065 | 50.0 | 1150 | 0.4331 | 0.7801 | 0.7129 | 0.745 | 0.9363 |
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  ### Framework versions
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