Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: answerdotai/ModernBERT-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: nci-binary-detector-v2
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# nci-binary-detector-v2
+
+This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0026
+- Accuracy: 0.9936
+- F1: 0.9944
+- Precision: 0.9889
+- Recall: 1.0
+- Roc Auc: 0.9989
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Roc Auc |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
+| 0.0232        | 0.1305 | 100  | 0.0114          | 0.9496   | 0.9575 | 0.9272    | 0.9899 | 0.9948  |
+| 0.0144        | 0.2609 | 200  | 0.0025          | 0.9925   | 0.9935 | 0.9890    | 0.9980 | 0.9997  |
+| 0.0074        | 0.3914 | 300  | 0.0037          | 0.9948   | 0.9955 | 0.9960    | 0.9949 | 0.9996  |
+| 0.0028        | 0.5219 | 400  | 0.0022          | 0.9971   | 0.9975 | 0.9960    | 0.9990 | 0.9995  |
+| 0.002         | 0.6523 | 500  | 0.0038          | 0.9942   | 0.9950 | 0.9910    | 0.9990 | 0.9983  |
+| 0.0004        | 0.7828 | 600  | 0.0023          | 0.9971   | 0.9975 | 0.9970    | 0.9980 | 0.9987  |
+| 0.0052        | 0.9132 | 700  | 0.0008          | 0.9959   | 0.9965 | 0.9930    | 1.0    | 1.0000  |
+
+
+### Framework versions
+
+- Transformers 4.57.3
+- Pytorch 2.9.1+cu128
+- Datasets 4.4.1
+- Tokenizers 0.22.1

model.safetensors

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