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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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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: my_awesome_wnut_model |
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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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# my_awesome_wnut_model |
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This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5795 |
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- Precision: 0.2438 |
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- Recall: 0.6759 |
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- F1: 0.3583 |
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- Accuracy: 0.8634 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 50 |
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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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| 1.5943 | 1.0 | 38 | 0.3653 | 0.1156 | 0.6069 | 0.1943 | 0.8489 | |
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| 1.5943 | 2.0 | 76 | 0.3859 | 0.2032 | 0.7034 | 0.3153 | 0.8691 | |
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| 0.2445 | 3.0 | 114 | 0.4085 | 0.2422 | 0.8069 | 0.3726 | 0.8679 | |
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| 0.2445 | 4.0 | 152 | 0.3778 | 0.2013 | 0.6345 | 0.3056 | 0.8733 | |
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| 0.2445 | 5.0 | 190 | 0.4417 | 0.2010 | 0.5448 | 0.2937 | 0.8755 | |
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| 0.0861 | 6.0 | 228 | 0.5795 | 0.2438 | 0.6759 | 0.3583 | 0.8634 | |
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### Framework versions |
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- Transformers 4.53.2 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
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