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modern-bert-finetuned-query-classification

Text Classification
Transformers
TensorBoard
ONNX
Safetensors
modernbert
Generated from Trainer
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Add model trained for query classification (v4.0)

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  1. README.md +11 -10
  2. model.safetensors +1 -1
  3. runs/Apr10_11-49-18_ef403fb20d9e/events.out.tfevents.1744285766.ef403fb20d9e.188.2 +2 -2
  4. runs/Apr10_11-49-18_ef403fb20d9e/events.out.tfevents.1744286461.ef403fb20d9e.188.3 +3 -0
README.md CHANGED
@@ -3,6 +3,7 @@ library_name: transformers
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  license: apache-2.0
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  base_model: answerdotai/ModernBERT-base
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  tags:
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -21,11 +22,11 @@ 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: 0.1951
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- - Accuracy: 0.9713
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- - F1: 0.9713
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- - Precision: 0.9724
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- - Recall: 0.9713
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  ## Model description
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@@ -56,11 +57,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 1.0 | 305 | 0.2426 | 0.9521 | 0.9520 | 0.9565 | 0.9521 |
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- | 0.1447 | 2.0 | 610 | 0.1809 | 0.9598 | 0.9600 | 0.9618 | 0.9598 |
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- | 0.1447 | 3.0 | 915 | 0.1568 | 0.9674 | 0.9676 | 0.9679 | 0.9674 |
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- | 0.0158 | 4.0 | 1220 | 0.2314 | 0.9674 | 0.9675 | 0.9694 | 0.9674 |
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- | 0.0022 | 5.0 | 1525 | 0.1951 | 0.9713 | 0.9713 | 0.9724 | 0.9713 |
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  ### Framework versions
 
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  license: apache-2.0
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  base_model: answerdotai/ModernBERT-base
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  tags:
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+ - v4.0
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
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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: 0.1555
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+ - Accuracy: 0.9789
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+ - F1: 0.9790
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+ - Precision: 0.9792
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+ - Recall: 0.9789
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 305 | 0.2230 | 0.9579 | 0.9579 | 0.9600 | 0.9579 |
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+ | 0.1385 | 2.0 | 610 | 0.1555 | 0.9789 | 0.9790 | 0.9792 | 0.9789 |
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+ | 0.1385 | 3.0 | 915 | 0.1744 | 0.9693 | 0.9694 | 0.9701 | 0.9693 |
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+ | 0.0189 | 4.0 | 1220 | 0.2378 | 0.9674 | 0.9675 | 0.9684 | 0.9674 |
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+ | 0.0022 | 5.0 | 1525 | 0.2181 | 0.9732 | 0.9733 | 0.9737 | 0.9732 |
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  ### Framework versions
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