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  1. README.md +10 -10
  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 [numind/NuNER-v2.0](https://huggingface.co/numind/NuNER-v2.0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2392
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- - Precision: 0.6818
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- - Recall: 0.7148
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- - F1: 0.6979
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- - Accuracy: 0.9309
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.2608 | 1.0 | 2059 | 0.2497 | 0.6512 | 0.7000 | 0.6747 | 0.9255 |
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- | 0.2153 | 2.0 | 4118 | 0.2364 | 0.6796 | 0.7015 | 0.6904 | 0.9302 |
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- | 0.1949 | 3.0 | 6177 | 0.2347 | 0.6785 | 0.7110 | 0.6944 | 0.9309 |
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- | 0.1669 | 4.0 | 8236 | 0.2392 | 0.6818 | 0.7148 | 0.6979 | 0.9309 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [numind/NuNER-v2.0](https://huggingface.co/numind/NuNER-v2.0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2362
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+ - Precision: 0.6810
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+ - Recall: 0.7160
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+ - F1: 0.6981
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+ - Accuracy: 0.9313
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2602 | 1.0 | 2059 | 0.2486 | 0.6570 | 0.7031 | 0.6793 | 0.9270 |
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+ | 0.2199 | 2.0 | 4118 | 0.2369 | 0.6791 | 0.7043 | 0.6915 | 0.9302 |
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+ | 0.2052 | 3.0 | 6177 | 0.2349 | 0.6785 | 0.7143 | 0.6959 | 0.9312 |
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+ | 0.1835 | 4.0 | 8236 | 0.2362 | 0.6810 | 0.7160 | 0.6981 | 0.9313 |
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  ### Framework versions
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