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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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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: modernbert-disfluency |
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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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# modernbert-disfluency |
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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: 0.1619 |
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- Precision: 0.8263 |
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- Recall: 0.7602 |
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- F1: 0.7919 |
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- Accuracy: 0.9556 |
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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: 4e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 128 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 49 | 0.3026 | 0.8905 | 0.5 | 0.6404 | 0.9178 | |
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| No log | 2.0 | 98 | 0.2426 | 0.8512 | 0.5861 | 0.6942 | 0.9340 | |
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| 0.4156 | 3.0 | 147 | 0.1860 | 0.8020 | 0.6721 | 0.7313 | 0.9464 | |
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| 0.4156 | 4.0 | 196 | 0.1633 | 0.8263 | 0.7602 | 0.7919 | 0.9556 | |
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| 0.1117 | 5.0 | 245 | 0.1810 | 0.8025 | 0.7992 | 0.8008 | 0.9554 | |
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| 0.1117 | 6.0 | 294 | 0.1832 | 0.782 | 0.8012 | 0.7915 | 0.9561 | |
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| 0.0401 | 7.0 | 343 | 0.1956 | 0.8043 | 0.7746 | 0.7891 | 0.9554 | |
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| 0.0401 | 8.0 | 392 | 0.1973 | 0.7864 | 0.7848 | 0.7856 | 0.9563 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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