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--- |
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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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model-index: |
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- name: nci-technique-classifier-v5.2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# nci-technique-classifier-v5.2 |
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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: 0.0173 |
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- Micro F1: 0.7718 |
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- Macro F1: 0.5789 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Micro F1 | Macro F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:| |
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| 0.0275 | 0.1570 | 200 | 0.0272 | 0.6634 | 0.2831 | |
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| 0.0256 | 0.3140 | 400 | 0.0238 | 0.6844 | 0.3147 | |
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| 0.0211 | 0.4710 | 600 | 0.0226 | 0.7276 | 0.2792 | |
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| 0.0224 | 0.6279 | 800 | 0.0206 | 0.7140 | 0.4159 | |
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| 0.0198 | 0.7849 | 1000 | 0.0203 | 0.7180 | 0.4403 | |
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| 0.0175 | 0.9419 | 1200 | 0.0192 | 0.7481 | 0.4333 | |
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| 0.018 | 1.0989 | 1400 | 0.0190 | 0.7320 | 0.4845 | |
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| 0.017 | 1.2559 | 1600 | 0.0191 | 0.7199 | 0.4723 | |
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| 0.0165 | 1.4129 | 1800 | 0.0188 | 0.7597 | 0.4633 | |
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| 0.0165 | 1.5699 | 2000 | 0.0182 | 0.7434 | 0.5247 | |
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| 0.0167 | 1.7268 | 2200 | 0.0183 | 0.7345 | 0.5005 | |
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| 0.0167 | 1.8838 | 2400 | 0.0182 | 0.7629 | 0.5162 | |
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| 0.0143 | 2.0408 | 2600 | 0.0180 | 0.7493 | 0.5557 | |
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| 0.016 | 2.1978 | 2800 | 0.0183 | 0.7588 | 0.5513 | |
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| 0.0157 | 2.3548 | 3000 | 0.0185 | 0.7663 | 0.5457 | |
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| 0.0157 | 2.5118 | 3200 | 0.0183 | 0.7665 | 0.5756 | |
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| 0.0146 | 2.6688 | 3400 | 0.0179 | 0.7641 | 0.5885 | |
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| 0.0123 | 2.8257 | 3600 | 0.0182 | 0.7719 | 0.5734 | |
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| 0.0136 | 2.9827 | 3800 | 0.0179 | 0.7682 | 0.5952 | |
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### Framework versions |
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- Transformers 4.57.3 |
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- Pytorch 2.9.1+cu128 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
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