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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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- accuracy |
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- f1 |
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model-index: |
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- name: MBERT-Clinc |
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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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# MBERT-Clinc |
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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: 0.1834 |
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- Accuracy: 0.9681 |
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- F1: 0.9677 |
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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-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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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: cosine |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
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| 1.5635 | 0.4193 | 200 | 0.4160 | 0.8932 | 0.8911 | |
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| 0.2762 | 0.8386 | 400 | 0.2421 | 0.9387 | 0.9371 | |
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| 0.1315 | 1.2579 | 600 | 0.3010 | 0.9390 | 0.9376 | |
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| 0.0801 | 1.6771 | 800 | 0.2305 | 0.9552 | 0.9547 | |
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| 0.0736 | 2.0964 | 1000 | 0.2306 | 0.9577 | 0.9573 | |
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| 0.0288 | 2.5157 | 1200 | 0.2389 | 0.9545 | 0.9532 | |
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| 0.0159 | 2.9350 | 1400 | 0.1933 | 0.9661 | 0.9656 | |
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| 0.0069 | 3.3543 | 1600 | 0.1857 | 0.9652 | 0.9648 | |
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| 0.0062 | 3.7736 | 1800 | 0.1807 | 0.9677 | 0.9674 | |
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| 0.0061 | 4.1929 | 2000 | 0.1841 | 0.9674 | 0.9671 | |
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| 0.0011 | 4.6122 | 2200 | 0.1834 | 0.9681 | 0.9677 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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