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joyle
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bert-finetuned-ner

Token Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
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Training complete

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  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. training_args.bin +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 [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0598
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- - Precision: 0.9356
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- - Recall: 0.9514
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- - F1: 0.9434
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- - Accuracy: 0.9869
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  ## Model description
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@@ -55,9 +55,9 @@ 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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- | 0.0728 | 1.0 | 1756 | 0.0622 | 0.9108 | 0.9369 | 0.9237 | 0.9832 |
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- | 0.0342 | 2.0 | 3512 | 0.0589 | 0.9388 | 0.9495 | 0.9441 | 0.9865 |
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- | 0.021 | 3.0 | 5268 | 0.0598 | 0.9356 | 0.9514 | 0.9434 | 0.9869 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0621
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+ - Precision: 0.9297
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+ - Recall: 0.9477
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+ - F1: 0.9386
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+ - Accuracy: 0.9864
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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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+ | 0.072 | 1.0 | 1756 | 0.0647 | 0.8982 | 0.9323 | 0.9149 | 0.9817 |
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+ | 0.0352 | 2.0 | 3512 | 0.0666 | 0.9305 | 0.9443 | 0.9374 | 0.9853 |
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+ | 0.0211 | 3.0 | 5268 | 0.0621 | 0.9297 | 0.9477 | 0.9386 | 0.9864 |
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  ### Framework versions
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