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ModernBERT-base-NER

Token Classification
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modernbert
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named-entity-recognition
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End of training

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  1. README.md +11 -10
  2. model.safetensors +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5320
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- - Precision: 0.8982
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- - Recall: 0.9239
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- - F1: 0.9109
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- - Accuracy: 0.9822
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  ## Model description
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@@ -50,16 +50,17 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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- - num_epochs: 3
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- - label_smoothing_factor: 0.1
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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 | 439 | 0.5504 | 0.8433 | 0.8847 | 0.8635 | 0.9749 |
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- | 0.6307 | 2.0 | 878 | 0.5335 | 0.8944 | 0.9204 | 0.9072 | 0.9818 |
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- | 0.5226 | 3.0 | 1317 | 0.5320 | 0.8982 | 0.9239 | 0.9109 | 0.9822 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0638
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+ - Precision: 0.8986
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+ - Recall: 0.9295
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+ - F1: 0.9138
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+ - Accuracy: 0.9840
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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+ - num_epochs: 5
 
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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 | 439 | 0.0820 | 0.8431 | 0.8899 | 0.8659 | 0.9766 |
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+ | 0.1769 | 2.0 | 878 | 0.0645 | 0.8895 | 0.9212 | 0.9051 | 0.9823 |
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+ | 0.0415 | 3.0 | 1317 | 0.0638 | 0.8986 | 0.9295 | 0.9138 | 0.9840 |
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+ | 0.0143 | 4.0 | 1756 | 0.0659 | 0.9037 | 0.9335 | 0.9184 | 0.9849 |
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+ | 0.0051 | 5.0 | 2195 | 0.0672 | 0.9041 | 0.9329 | 0.9182 | 0.9849 |
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  ### Framework versions
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