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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-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: binary_paragraph |
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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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# binary_paragraph |
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2458 |
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- Classification Report: {'0': {'precision': 0.930564166150031, 'recall': 0.9428391959798995, 'f1-score': 0.9366614664586583, 'support': 1592.0}, '1': {'precision': 0.6192468619246861, 'recall': 0.5692307692307692, 'f1-score': 0.593186372745491, 'support': 260.0}, 'accuracy': 0.8903887688984882, 'macro avg': {'precision': 0.7749055140373586, 'recall': 0.7560349826053343, 'f1-score': 0.7649239196020747, 'support': 1852.0}, 'weighted avg': {'precision': 0.8868587130730388, 'recall': 0.8903887688984882, 'f1-score': 0.8884414209049739, 'support': 1852.0}} |
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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: 5e-06 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 256 |
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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: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Classification Report | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| |
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| No log | 1.0 | 25 | 0.2760 | {'0': {'precision': 0.8786867000556483, 'recall': 0.9918341708542714, 'f1-score': 0.9318383003835939, 'support': 1592.0}, '1': {'precision': 0.7636363636363637, 'recall': 0.16153846153846155, 'f1-score': 0.26666666666666666, 'support': 260.0}, 'accuracy': 0.8752699784017278, 'macro avg': {'precision': 0.8211615318460059, 'recall': 0.5766863161963665, 'f1-score': 0.5992524835251303, 'support': 1852.0}, 'weighted avg': {'precision': 0.8625349249643881, 'recall': 0.8752699784017278, 'f1-score': 0.8384556736198784, 'support': 1852.0}} | |
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| No log | 2.0 | 50 | 0.2626 | {'0': {'precision': 0.8689240851993446, 'recall': 0.9993718592964824, 'f1-score': 0.9295939234589541, 'support': 1592.0}, '1': {'precision': 0.9523809523809523, 'recall': 0.07692307692307693, 'f1-score': 0.1423487544483986, 'support': 260.0}, 'accuracy': 0.8698704103671706, 'macro avg': {'precision': 0.9106525187901484, 'recall': 0.5381474681097796, 'f1-score': 0.5359713389536763, 'support': 1852.0}, 'weighted avg': {'precision': 0.8806404920390952, 'recall': 0.8698704103671706, 'f1-score': 0.81907354336028, 'support': 1852.0}} | |
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| No log | 3.0 | 75 | 0.2458 | {'0': {'precision': 0.930564166150031, 'recall': 0.9428391959798995, 'f1-score': 0.9366614664586583, 'support': 1592.0}, '1': {'precision': 0.6192468619246861, 'recall': 0.5692307692307692, 'f1-score': 0.593186372745491, 'support': 260.0}, 'accuracy': 0.8903887688984882, 'macro avg': {'precision': 0.7749055140373586, 'recall': 0.7560349826053343, 'f1-score': 0.7649239196020747, 'support': 1852.0}, 'weighted avg': {'precision': 0.8868587130730388, 'recall': 0.8903887688984882, 'f1-score': 0.8884414209049739, 'support': 1852.0}} | |
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### Framework versions |
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- Transformers 4.52.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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