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tr-aravindan
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bert-finetuned-ner

Token Classification
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bert
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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/Mar05_16-26-15_e94c8e0ede6b/events.out.tfevents.1709655979.e94c8e0ede6b.4300.0 +2 -2
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: 0.0585
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- - Precision: 0.9362
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- - Recall: 0.9509
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- - F1: 0.9435
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- - Accuracy: 0.9864
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  ## Model description
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@@ -55,14 +55,14 @@ 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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- | 0.0799 | 1.0 | 1756 | 0.0809 | 0.9092 | 0.9332 | 0.9210 | 0.9789 |
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- | 0.0402 | 2.0 | 3512 | 0.0574 | 0.9263 | 0.9473 | 0.9367 | 0.9858 |
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- | 0.0255 | 3.0 | 5268 | 0.0585 | 0.9362 | 0.9509 | 0.9435 | 0.9864 |
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  ### Framework versions
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- - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.16.1
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- - Tokenizers 0.15.1
 
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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: 0.0604
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+ - Precision: 0.9338
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+ - Recall: 0.9519
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+ - F1: 0.9427
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+ - Accuracy: 0.9867
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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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+ | 0.0737 | 1.0 | 1756 | 0.0732 | 0.9033 | 0.9334 | 0.9181 | 0.9800 |
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+ | 0.0363 | 2.0 | 3512 | 0.0645 | 0.9310 | 0.9446 | 0.9378 | 0.9857 |
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+ | 0.0224 | 3.0 | 5268 | 0.0604 | 0.9338 | 0.9519 | 0.9427 | 0.9867 |
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  ### Framework versions
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+ - Transformers 4.38.1
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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