End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: answerdotai/ModernBERT-base
+tags:
+- generated_from_trainer
+model-index:
+- name: nci-technique-classifier-v5.2
+  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-technique-classifier-v5.2
+
+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: 0.0173
+- Micro F1: 0.7718
+- Macro F1: 0.5789
+
+## 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
+- 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: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Micro F1 | Macro F1 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|
+| 0.0275        | 0.1570 | 200  | 0.0272          | 0.6634   | 0.2831   |
+| 0.0256        | 0.3140 | 400  | 0.0238          | 0.6844   | 0.3147   |
+| 0.0211        | 0.4710 | 600  | 0.0226          | 0.7276   | 0.2792   |
+| 0.0224        | 0.6279 | 800  | 0.0206          | 0.7140   | 0.4159   |
+| 0.0198        | 0.7849 | 1000 | 0.0203          | 0.7180   | 0.4403   |
+| 0.0175        | 0.9419 | 1200 | 0.0192          | 0.7481   | 0.4333   |
+| 0.018         | 1.0989 | 1400 | 0.0190          | 0.7320   | 0.4845   |
+| 0.017         | 1.2559 | 1600 | 0.0191          | 0.7199   | 0.4723   |
+| 0.0165        | 1.4129 | 1800 | 0.0188          | 0.7597   | 0.4633   |
+| 0.0165        | 1.5699 | 2000 | 0.0182          | 0.7434   | 0.5247   |
+| 0.0167        | 1.7268 | 2200 | 0.0183          | 0.7345   | 0.5005   |
+| 0.0167        | 1.8838 | 2400 | 0.0182          | 0.7629   | 0.5162   |
+| 0.0143        | 2.0408 | 2600 | 0.0180          | 0.7493   | 0.5557   |
+| 0.016         | 2.1978 | 2800 | 0.0183          | 0.7588   | 0.5513   |
+| 0.0157        | 2.3548 | 3000 | 0.0185          | 0.7663   | 0.5457   |
+| 0.0157        | 2.5118 | 3200 | 0.0183          | 0.7665   | 0.5756   |
+| 0.0146        | 2.6688 | 3400 | 0.0179          | 0.7641   | 0.5885   |
+| 0.0123        | 2.8257 | 3600 | 0.0182          | 0.7719   | 0.5734   |
+| 0.0136        | 2.9827 | 3800 | 0.0179          | 0.7682   | 0.5952   |
+
+
+### 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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