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bert-base-finetuned-ner

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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@@ -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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3723
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- - Precision: 0.5534
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- - Recall: 0.5362
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- - F1: 0.5447
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- - Accuracy: 0.9281
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  ## Model description
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@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
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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 | 121 | 0.4063 | 0.2711 | 0.2638 | 0.2674 | 0.8968 |
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- | No log | 2.0 | 242 | 0.3501 | 0.4935 | 0.3220 | 0.3897 | 0.9196 |
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- | No log | 3.0 | 363 | 0.2928 | 0.4839 | 0.4255 | 0.4528 | 0.9272 |
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- | No log | 4.0 | 484 | 0.3419 | 0.5407 | 0.3957 | 0.4570 | 0.9247 |
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- | 0.3258 | 5.0 | 605 | 0.3310 | 0.5431 | 0.4553 | 0.4954 | 0.9294 |
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- | 0.3258 | 6.0 | 726 | 0.3424 | 0.5248 | 0.4809 | 0.5019 | 0.9274 |
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- | 0.3258 | 7.0 | 847 | 0.3587 | 0.5471 | 0.5191 | 0.5328 | 0.9309 |
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- | 0.3258 | 8.0 | 968 | 0.3639 | 0.5396 | 0.5220 | 0.5306 | 0.9281 |
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- | 0.1033 | 9.0 | 1089 | 0.3695 | 0.5471 | 0.5277 | 0.5372 | 0.9276 |
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- | 0.1033 | 10.0 | 1210 | 0.3723 | 0.5534 | 0.5362 | 0.5447 | 0.9281 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3788
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+ - Precision: 0.5395
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+ - Recall: 0.5234
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+ - F1: 0.5313
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+ - Accuracy: 0.9307
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  ## Model description
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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 | 121 | 0.4099 | 0.2393 | 0.2383 | 0.2388 | 0.8962 |
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+ | No log | 2.0 | 242 | 0.3394 | 0.4340 | 0.3220 | 0.3697 | 0.9180 |
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+ | No log | 3.0 | 363 | 0.2952 | 0.5017 | 0.4170 | 0.4555 | 0.9271 |
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+ | No log | 4.0 | 484 | 0.3419 | 0.5301 | 0.4 | 0.4559 | 0.9284 |
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+ | 0.321 | 5.0 | 605 | 0.3269 | 0.5354 | 0.4723 | 0.5019 | 0.9313 |
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+ | 0.321 | 6.0 | 726 | 0.3382 | 0.5091 | 0.4780 | 0.4931 | 0.9285 |
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+ | 0.321 | 7.0 | 847 | 0.3528 | 0.5489 | 0.5177 | 0.5328 | 0.9315 |
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+ | 0.321 | 8.0 | 968 | 0.3623 | 0.5446 | 0.5191 | 0.5316 | 0.9306 |
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+ | 0.0997 | 9.0 | 1089 | 0.3706 | 0.5225 | 0.5262 | 0.5244 | 0.9283 |
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+ | 0.0997 | 10.0 | 1210 | 0.3788 | 0.5395 | 0.5234 | 0.5313 | 0.9307 |
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  ### Framework versions